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Python Tutorial: Anaconda - Installation and Using Conda
 
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In this Python Tutorial, we will be learning how to install Anaconda by Continuum Analytics. Anaconda is a data science platform that comes with a lot of useful features right out of the box. Many people find that installing Python through Anaconda is much easier than doing so manually. Also, we will look at Conda. Conda is Continuum's package, dependency and environment manager. Let's get started. Anaconda Download Page: https://www.anaconda.com/download/ If you enjoy these videos and would like to support my channel, I would greatly appreciate any assistance through my Patreon account: https://www.patreon.com/coreyms Or a one-time contribution through PayPal: https://goo.gl/649HFY If you would like to see additional ways in which you can support the channel, you can check out my support page: http://coreyms.com/support/ You can find me on: My website - http://coreyms.com/ Facebook - https://www.facebook.com/CoreyMSchafer Twitter - https://twitter.com/CoreyMSchafer Google Plus - https://plus.google.com/+CoreySchafer44/posts Tumblr - https://www.tumblr.com/blog/mycms
Views: 442019 Corey Schafer
The Top 5 #MachineLearning Libraries in #Python
 
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How to Install Masternode for Geek Cash ☞ https://codequs.com/p/HyZO2Elg7 Get Free 15 Geek ☞ https://my.geekcash.io/ref/5b3c4924d38b6158ce04633f Free trading fees in the first year ☞ https://aiodex.com/?ref=5b45a599c7165734d36bb3fc Machine Learning A-Z™: Hands-On Python & R In Data Science ☞ http://deal.codetrick.net/p/SJw1YoTMg Python for Data Science and Machine Learning Bootcamp ☞ http://deal.codetrick.net/p/BJzWmGFGg Data Science, Deep Learning, & Machine Learning with Python ☞ http://deal.codetrick.net/p/BkS5nEmZg Deep Learning A-Z™: Hands-On Artificial Neural Networks ☞ http://deal.codetrick.net/p/BkhKBKGFW Bayesian Machine Learning in Python: A/B Testing ☞ http://deal.codetrick.net/p/r1x29vqfx The Complete SQL Bootcamp ☞ http://deal.codetrick.net/p/HJH7nHmre Tableau 10 A-Z: Hands-On Tableau Training For Data Science! ☞ http://deal.codetrick.net/p/H11NbFMYZ A Gentle Introduction to the Top Python Libraries used in Applied Machine Learning Recent Review from Similar Course: "This was one of the most useful classes I have taken in a long time. Very specific, real-world examples. It covered several instances of 'what is happening', 'what it means' and 'how you fix it'. I was impressed." Steve Welcome to The Top 5 Machine Learning Libraries in Python. This is an introductory course on the process of building supervised machine learning models and then using libraries in a computer programming language called Python. What’s the top career in the world? Doctor? Lawyer? Teacher? Nope. None of those. The top career in the world is the data scientist. Great. What’s a data scientist? The area of study which involves extracting knowledge from data is called Data Science and people practicing in this field are called as Data Scientists. Business generate a huge amount of data. The data has tremendous value but there so much of it where do you begin to look for value that is actionable? That’s where the data scientist comes in. The job of the data scientist is to create predictive models that can find hidden patterns in data that will give the business a competitive advantage in their space. Don’t I need a PhD? Nope. Some data scientists do have PhDs but it’s not a requirement. A similar career to that of the data scientist is the machine learning engineer. A machine learning engineer is a person who builds predictive models, scores them and then puts them into production so that others in the company can consume or use their model. They are usually skilled programmers that have a solid background in data mining or other data related professions and they have learned predictive modeling. In the course we are going to take a look at what machine learning engineers do. We are going to learn about the process of building supervised predictive models and build several using the most widely used programming language for machine learning. Python. There are literally hundreds of libraries we can import into Python that are machine learning related. A library is simply a group of code that lives outside the core language. We “import it” into our work space when we need to use its functionality. We can mix and match these libraries like Lego blocks. Thanks for your interest in the The Top 5 Machine Learning Libraries in Python and we will see you in the course. Who is the target audience? If you're looking to learn machine learning then this course is for you. Video source viva: Udemy ---------------------------------------------------- Website: http://bit.ly/2pN2aXx Playlist: http://bit.ly/2Eyn3dI Website: http://bit.ly/2Hay229 Fanpage: http://bit.ly/2qi5j1A Twitter: http://bit.ly/2GOyTlA Pinterest: http://bit.ly/2qihWtz Tumblr: http://bit.ly/2qjBcGo
Views: 316 coderschool
Data Analysis with Python and Pandas Tutorial Introduction
 
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Pandas is a Python module, and Python is the programming language that we're going to use. The Pandas module is a high performance, highly efficient, and high level data analysis library. At its core, it is very much like operating a headless version of a spreadsheet, like Excel. Most of the datasets you work with will be what are called dataframes. You may be familiar with this term already, it is used across other languages, but, if not, a dataframe is most often just like a spreadsheet. Columns and rows, that's all there is to it! From here, we can utilize Pandas to perform operations on our data sets at lightning speeds. Sample code: http://pythonprogramming.net/data-analysis-python-pandas-tutorial-introduction/ Pip install tutorial: http://pythonprogramming.net/using-pip-install-for-python-modules/ Matplotlib series starts here: http://pythonprogramming.net/matplotlib-intro-tutorial/
Views: 395458 sentdex
Python Bitcoin Tutorial for Beginners
 
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My Book: https://www.amazon.com/Building-Bitcoin-Websites-Beginners-Development/dp/153494544X A simple introduction tutorial to get started with the pybitcointools Python library. https://github.com/vbuterin/pybitcointools
Views: 51172 m1xolyd1an
Mining data on Facebook with Python: 1- Setting up our app for mining data on Facebook
 
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In this tutorial we will set up our app to mine data from Facebook. We will be introduces to the Facebook API Graph and setting up user token access. Let's connect out app to communicate with the Graph API to get started mining data on this huge platform. ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 11998 Sukhvinder Singh
Import Data and Analyze with Python
 
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Python programming language allows sophisticated data analysis and visualization. This tutorial is a basic step-by-step introduction on how to import a text file (CSV), perform simple data analysis, export the results as a text file, and generate a trend. See https://youtu.be/pQv6zMlYJ0A for updated video for Python 3.
Views: 177695 APMonitor.com
WEB SCRAPING WITH SCRAPY - INTRODUCTION AND SETUP
 
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Join us for our new series that will teach you how to get started web scraping by using the Scrapy library. Web scraping can be an important tool for your data science career and be able to know how to build your own data or collect data by web scraping is essential to help grow and become even more efficient. The Scrapy library (Scrapy.org) is “An open source and collaborative framework for extracting the data you need from websites. In a fast, simple, yet extensible way.” This series will go through some of the key elements of web scraping such as understanding HTML, CSS and web elements, it will show you how to integrate Anaconda into your development environment and a range of other useful information. It will also go on to show you how to inspect a web page to extract crucial data and build your own custom web spiders or crawlers that can go out and retrieve data. Come join this fun and informative series and get started web scraping today!
Views: 10957 SuperDataScience
Twitter Data Mining using Python
 
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For complete professional training visit at: http://www.bisptrainings.com/course/Python-for-Beginners Follow us on Facebook: https://www.facebook.com/bisptrainings/ Follow us on Twitter: https://twitter.com/bisptrainings Email: [email protected] Call us: +91 975-275-3753 or +1 386-279-6856
Views: 25499 Amit Sharma
Raspberry Pi show real time sensor data in a graph Python
 
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small tutorial about installing python libraries on the raspberry pi. And get a temperature data from a DHT sensor. And show this data in a real time update graph. Matplotlib linkt to code: https://create.arduino.cc/editor/LogMaker360/b6f3d6dd-ae21-46ea-af75-38be4caebba6/preview
Views: 30566 logMaker360
Top 10 Python Libraries | Python Certification Training for Data Science | Edureka
 
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***** Python Certification Training for Data Science : https://www.edureka.co/python ***** This Edureka live session will introduce you to the top 10 most trending Python libraries. The 10 python libraries included in this session are: 1. TensorFlow 2. Scikit-learn 3. SciPy 4. NumPy 5. Pandas 6. Selenium 7. PySpark 8. OpenCV 9. Matplotlib 10. Django Subscribe to our channel to get video updates. Hit the subscribe button above. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - - - - About the Course Edureka’s Python Data Science course is designed to make you grab the concepts of Machine Learning. The course will provide deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in python programming language. Furthermore, you will be taught of Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real life scenarios using Machine Learning Algorithms. Towards the end of the course we will be discussing various practical use cases of Machine Learning in python programming language to enhance your learning experience. - - - - - - - - - - - - - - - - - - - Why learn Data Science? Data Science is a set of techniques that enables the computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms. This course imparts you the necessary skills like data pre-processing, dimensional reduction, model evaluation and also exposes you to different machine learning algorithms like regression, clustering, decision trees, random forest, Naive Bayes and Q-Learning.
Views: 7248 edureka!
Python Generate Fake Data with Faker Package
 
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In this Python tutorial, we will go over how to generate fake data. Fake data can be useful when you need data to help learn about programming language features, you need sample data to import into a new software program to learn how to use the software (i.e.-visualize data), test a database, generate fake data to test spreadsheet functions, etc. We will be using the Python Faker Package to create fake data. We will also go over where you can gain access to the Python Faker Package. As always, before you download anything, make sure you are on the correct/intended site and that the site and download source are safe and secure.
Views: 1672 Ryan Noonan
Python for Data Analysis and Visualization | Webinar by Vinod Venkatraman | Hackerearth
 
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About the webinar: Data analytics using Python's numpy, scikit, pandas modules Data Visualisation using Python's matplotlib module Big Data Analytics using PySpark with spark-core and mllib About the Speaker: The Speaker is Vinod Venkatraman. A passionate technology man of multiple talents, Vinod is spearheading the core technology initiatives at Great Learning. Be it a seamless user experience, the collection of thousands of critical user action data points daily or rolling out a great new feature, Vinod obsesses about it as fervently as he does create a new tune on his guitar. Vinod holds a B.Tech from IIT Bombay in Computer Science. He spent 7 years at Stratify Inc, a Silicon Valley-based product firm, to start his career, followed by 4 years at Flipkart, where he rose to be Software Architect. He now looks forward to leading the effort to build his own unicorn. Subscribe Our Channel For More Updates : https://goo.gl/suzeTB For More Updates, Please follow us on : Facebook : https://goo.gl/40iEqB Twitter : https://goo.gl/LcTAsM LinkedIn : https://goo.gl/iQCgJh Blog : https://goo.gl/9yOzvG
Views: 2305 HackerEarth
Machine Learning for Time Series Data in Python | SciPy 2016 | Brett Naul
 
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The analysis of time series data is a fundamental part of many scientific disciplines, but there are few resources meant to help domain scientists to easily explore time course datasets: traditional statistical models of time series are often too rigid to explain complex time domain behavior, while popular machine learning packages deal almost exclusively with 'fixed-width' datasets containing a uniform number of features. Cesium is a time series analysis framework, consisting of a Python library as well as a web front-end interface, that allows researchers to apply modern machine learning techniques to time series data in a way that is simple, easily reproducible, and extensible.
Views: 35372 Enthought
Scrape Websites with Python + Beautiful Soup 4 + Requests -- Coding with Python
 
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Coding with Python -- Scrape Websites with Python + Beautiful Soup + Python Requests Scraping websites for data is often a great way to do research on any given idea. This tutorial takes you through the steps of using the Python libraries Beautiful Soup 4 (http://www.crummy.com/software/BeautifulSoup/bs4/doc/#) and Python Requests (http://docs.python-requests.org/en/latest/). Reference code available under "Actions" here: https://codingforentrepreneurs.com/projects/coding-python/scrape-beautiful-soup/ Coding for Python is a series of videos designed to help you better understand how to use python. Assumes basic knowledge of python. View all my videos: http://bit.ly/1a4Ienh Join our Newsletter: http://eepurl.com/NmMcr A few ways to learn Django, Python, Jquery, and more: Coding For Entrepreneurs: https://codingforentrepreneurs.com (includes free projects and free setup guides. All premium content is just $25/mo). Includes implementing Twitter Bootstrap 3, Stripe.com, django, south, pip, django registration, virtual environments, deployment, basic jquery, ajax, and much more. On Udemy: Bestselling Udemy Coding for Entrepreneurs Course: https://www.udemy.com/coding-for-entrepreneurs/?couponCode=youtubecfe49 (reg $99, this link $49) MatchMaker and Geolocator Course: https://www.udemy.com/coding-for-entrepreneurs-matchmaker-geolocator/?couponCode=youtubecfe39 (advanced course, reg $75, this link: $39) Marketplace & Dail Deals Course: https://www.udemy.com/coding-for-entrepreneurs-marketplace-daily-deals/?couponCode=youtubecfe39 (advanced course, reg $75, this link: $39) Free Udemy Course (80k+ students): https://www.udemy.com/coding-for-entrepreneurs-basic/ Fun Fact! This Course was Funded on Kickstarter: http://www.kickstarter.com/projects/jmitchel3/coding-for-entrepreneurs
Views: 385183 CodingEntrepreneurs
Data Analysis with Python for Excel Users
 
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A common task for scientists and engineers is to analyze data from an external source. By importing the data into Python, data analysis such as statistics, trending, or calculations can be made to synthesize the information into relevant and actionable information. See http://apmonitor.com/che263/index.php/Main/PythonDataAnalysis
Views: 134744 APMonitor.com
Getting Started with Google APIs (Python)
 
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In this session, we build and deploy a simple App Engine application using Google APIs (eg. Google+ API) and OAuth2. We also demonstrate use of APIs Explorer, Quickstart widget, client libraries and App Engine SDK tools that make application development easier. This session demonstrated by Prashant Labhane is in Python and you can find the equivalent Java version at http://www.youtube.com/watch?v=tVIIgcIqoPw by Sachin Kotwani. You can find more references about Google Cloud development at developers.google.com and cloud.google.com.
Views: 113116 Google Developers
Introduction to Data Mining and Text Mining #2 (Python & Jupyter)
 
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Introduction to Data Mining and Text Mining - Part 2 - Python Introduction - Anaconda Installation (Data Science Distribution of Python) - Jupyter Introduction (Next Generation Engineering Notebook) “Hello World!” in Jupyter, and so on. by Kanda Tiwatthanont (Phawattanakul)
Views: 1005 Kanda
Data Analysis With Python In Visual Studio
 
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I walk through usage of NumPy, Pandas, and PyPlot in VS2013.
Views: 6207 Joel Holder
What is Numpy? Python for Data Science tutorial
 
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What is Numpy? Python for Data Science, data mining, data analysis tutorial This video is an introduction to the python package "Numpy" or numeric python. This video explains how regular python list is different from Numpy Arrays along with the examples on Pycharm. It also covers the basics of regular python list. Introduction to Python Lists : https://www.youtube.com/watch?v=7fp8-xJCHIk Video by Aditya Ekawade.
Views: 26856 i am biomed
Intro to Web Scraping with Python and Beautiful Soup
 
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Web scraping is a very powerful tool to learn for any data professional. With web scraping the entire internet becomes your database. In this tutorial we show you how to parse a web page into a data file (csv) using a Python package called BeautifulSoup. In this example, we web scrape graphics cards from NewEgg.com. Sublime: https://www.sublimetext.com/3 Anaconda: https://www.continuum.io/downloads#wi... -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 2700+ from over 400 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: http://bit.ly/2mgzx27 See what our past attendees are saying here: http://bit.ly/2nhE82P -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... Vimeo: https://vimeo.com/datasciencedojo
Views: 353103 Data Science Dojo
Predicting Stock Prices - Learn Python for Data Science #4
 
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In this video, we build an Apple Stock Prediction script in 40 lines of Python using the scikit-learn library and plot the graph using the matplotlib library. The challenge for this video is here: https://github.com/llSourcell/predicting_stock_prices Victor's winning recommender code: https://github.com/ciurana2016/recommender_system_py Kevin's runner-up code: https://github.com/Krewn/learner/blob/master/FieldPredictor.py#L62 I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Stock prediction with Tensorflow: https://nicholastsmith.wordpress.com/2016/04/20/stock-market-prediction-using-multi-layer-perceptrons-with-tensorflow/ Another great stock prediction tutorial: http://eugenezhulenev.com/blog/2014/11/14/stock-price-prediction-with-big-data-and-machine-learning/ This guy made 500K doing ML stuff with stocks: http://jspauld.com/post/35126549635/how-i-made-500k-with-machine-learning-and-hft Please share this video, like, comment and subscribe! That's what keeps me going. and please support me on Patreon!: https://www.patreon.com/user?u=3191693 Check out this youtube channel for some more cool Python tutorials: https://www.youtube.com/watch?v=RZF17FfRIIo Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
Views: 446520 Siraj Raval
Jupyter Project: Interacting between Python and R Libraries for Data Mining
 
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Myles Gartland http://www.pyvideo.org/video/3542/jupyter-project This talk will cover using ipython (Jupyter Project) for python and non-python projects, and how to interact Python and R through rmagic (rpy2) package.
Views: 5497 Next Day Video
Data analysis in Python with pandas
 
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Wes McKinney The tutorial will give a hands-on introduction to manipulating and analyzing large and small structured data sets in Python using the pandas library. While the focus will be on learning the nuts and bolts of the library's features, I als
Views: 282426 Next Day Video
Python For Data Analysis | Python Pandas Tutorial | Learn Python | Python Training | Edureka
 
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( Python Training : https://www.edureka.co/python ) This Edureka Python Pandas tutorial (Python Tutorial Blog: https://goo.gl/wd28Zr) will help you learn the basics of Pandas. It also includes a use-case, where we will analyse the data containing the percentage of unemployed youth for every country between 2010-2014. This Python Pandas tutorial video helps you to learn following topics: 1. What is Data Analysis? 2. What is Pandas? 3. Pandas Operations 4. Use-case Check out our Python Training Playlist: https://goo.gl/Na1p9G Subscribe to our channel to get video updates. Hit the subscribe button above. #Python #Pythontutorial #Pythononlinetraining #Pythonforbeginners #PythonProgramming #PythonPandas How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, please write back to us at [email protected] Call us at US: 1844 230 6362(toll free) or India: +91-90660 20867 Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 101870 edureka!
MSCI 723 Big Data Analytics Tut6: Association Rule Learning, Apriori Algorithm
 
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Hello everyone, this week in the tutorial we covered association rule learning and some apriori algorithm implementations I also introduced Orange, an open source data visualization and data analysis with interactive workflows and a large toolbox. Orange provides a Python library as week as an interface interface for data mining! Orange: http://orange.biolab.si/getting-started/ http://orange.biolab.si/screenshots/ http://orange.biolab.si/docs/latest/widgets/rst/ Tutorial: http://nbviewer.jupyter.org/github/datascienceguide/datascienceguide.github.io/blob/master/tutorials/Association-Rule-Mining.ipynb
Views: 7033 Andrew Andrade
How to Use the External Python Interpreter in the GOM Software 2018
 
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What's New GOM Software 2018: The GOM software offers fast and simplified data access for complex scientific computations using Python. Freely available Python libraries, such as NumPy, SciPy or Matplotlib, can be easily used with an external Python installation. Thus, both computations and diagrams can be created directly, which are necessary for, for example, vibration analyses (FFT) and tensile tests. The video tutorial shows how to use a standard Python installation for scripting in GOM Software and how to create a simple vibration analysis script with NumPy and Matplotlib. Try out the external Python interpreter and get further eLearning material about this topic: https://support.gom.com/x/rICxAw Provide feedback: https://support.gom.com/x/lICiAw
Views: 586 GOM Metrology
Natural Language Processing With Python and NLTK p.1 Tokenizing words and Sentences
 
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Natural Language Processing is the task we give computers to read and understand (process) written text (natural language). By far, the most popular toolkit or API to do natural language processing is the Natural Language Toolkit for the Python programming language. The NLTK module comes packed full of everything from trained algorithms to identify parts of speech to unsupervised machine learning algorithms to help you train your own machine to understand a specific bit of text. NLTK also comes with a large corpora of data sets containing things like chat logs, movie reviews, journals, and much more! Bottom line, if you're going to be doing natural language processing, you should definitely look into NLTK! Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1 sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
Views: 351305 sentdex
Data Analysis with Python for Excel User Part 1  Read and Write Excel File using Pandas
 
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Data Analysis with Python for Excel User Part 1 Read and Write Excel File using Pandas In this video we are going to learn how to read excel file using pandas Python is a widely used high-level, general-purpose, interpreted, dynamic programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than possible in languages such as C++ or Java. The language provides constructs intended to enable writing clear programs on both a small and large scale. Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles.It also supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed. The next part: https://youtu.be/-QKaVu_ebVY If you want to code in python for excel which the syntax is similar to VBA, you can go to this playlist: https://www.youtube.com/playlist?list=PL902m_5hKTbyJ4tnM0ax-7AI7VePas2QS Our money manager android app: https://play.google.com/store/apps/details?id=com.leazzy.moneymanagerleazzy
Views: 36884 Peasy Tutorial
How to read Excel files with Python (xlrd tutorial)
 
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Learn how to read out data from an Excel document using the xlrd Python module. The xlsx and xls file formats are supported. xlrd docs: http://www.lexicon.net/sjmachin/xlrd.html Type Numbers: 0 - XL_CELL_EMPTY 1 - XL_CELL_TEXT 2 - XL_CELL_NUMBER 3 - XL_CELL_DATE 4 - XL_CELL_BOOLEAN 5 - XL_CELL_ERROR 6 - XL_CELL_BLANK
Views: 166414 triforcelink
Data Science with Python and the Shiny Tools of Anaconda
 
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An ideal Python distribution for data analysis and data science is Anaconda which not only comes with the most important machine learning, data wrangling, and visualization libraries but some cool other tools to boot! in this video, we'll explain how to download and install Anaconda and discuss its features.
Views: 221 Bryan Cafferky
Intel® Distribution for Python – Highlights & Overview | Intel Software
 
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Get high performance Python at your fingertips with the free Intel® Distribution for Python. Intel released the Intel® Distribution for Python* in September 2016, and it has made a huge impact in advancing the performance of Python closer to native code. In this video, Sergey will highlight the many performance optimizations and enhancements that are included such as NumPy & SciPy performance optimizations with the Intel® Math Kernel Library, scikit-learn optimizations with Intel® Data Analytics Acceleration Library, NumPy memory optimizations and composable parallelism opportunities with TBB package. Learn how Intel contributes to the Python community by making these optimizations available through multiple channels. Intel® Distribution for Python* Home Page: http://intel.ly/2rWmGrH Intel® Distribution for Python* Home Page Benchmarks: http://intel.ly/2rVTLnV Intel® Distribution for Python* 2017 Update 2 Accelerates Five Key Areas for Impressive Performance Gains: http://intel.ly/2sv0Ry9 Intel® Distribution for Python* Forum: http://intel.ly/2rVFUOk Intel® Distribution for Python* Docker Hub: http://dockr.ly/2rWdIuG Anaconda.org: http://bit.ly/2rWubPp Intel® Math Kernel Library Home Page: http://intel.ly/2rW8OOl SUBSCRIBE NOW: http://bit.ly/2iZTCsz About Intel Software: The Intel® Developer Zone encourages and supports software developers that are developing applications for Intel hardware and software products. The Intel Software YouTube channel is a place to learn tips and tricks, get the latest news, watch product demos from both Intel, and our many partners across multiple fields. You'll find videos covering the topics listed below, and to learn more you can follow the links provided! Connect with Intel Software: Visit INTEL SOFTWARE WEBSITE: https://software.intel.com/en-us Like INTEL SOFTWARE on FACEBOOK: http://bit.ly/2z8MPFF Follow INTEL SOFTWARE on TWITTER: http://bit.ly/2zahGSn INTEL SOFTWARE GITHUB: http://bit.ly/2zaih6z INTEL DEVELOPER ZONE LINKEDIN: http://bit.ly/2z979qs INTEL DEVELOPER ZONE INSTAGRAM: http://bit.ly/2z9Xsby INTEL GAME DEV TWITCH: http://bit.ly/2BkNshu Intel® Distribution for Python – Highlights & Overview | Intel Softwarerfg279VgtDY
Views: 49242 Intel Software
Python for Data Science | Python Data Science Tutorial | Data Science Certification | Edureka
 
58:23
( Python Data Science Training : https://www.edureka.co/python ) This Edureka video on "Python For Data Science" explains the fundamental concepts of data science using python. It will also help you to analyze, manipulate and implement machine learning using various python libraries such as NumPy, Pandas and Scikit-learn. This video helps you to learn the below topics: 1. Need of Data Science 2. What is Data Science? 3. How Python is used for Data Science? 4. Data Manipulation in Python 5. Implement Machine Learning using Python 6. Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check out our Python Training Playlist: https://goo.gl/Na1p9G #Python #PythonForDataScience #PythonTutorial #PythonForBeginners #PythonOnlineTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka’s Data Science Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Data Science Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR. During our Python Certification Training, our instructors will help you to: 1. Master the basic and advanced concepts of Python 2. Gain insight into the 'Roles' played by a Machine Learning Engineer 3. Automate data analysis using python 4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 6. Explain Time Series and it’s related concepts 7. Perform Text Mining and Sentimental analysis 8. Gain expertise to handle business in future, living the present 9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, please write back to us at [email protected] Call us at US: 1844 230 6362(toll free) or India: +91-90660 20867 Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 17204 edureka!
Web scraping in Python (Part 3): Building a dataset
 
11:31
This is part 3 of an introductory web scraping tutorial. In this video, we'll create a structured dataset from a New York Times article using Python's Beautiful Soup library. Watch the 4-video series: https://www.youtube.com/playlist?list=PL5-da3qGB5IDbOi0g5WFh1YPDNzXw4LNL == RESOURCES == Download the Jupyter notebook: https://github.com/justmarkham/trump-lies New York Times article: https://www.nytimes.com/interactive/2017/06/23/opinion/trumps-lies.html Beautiful Soup documentation: https://www.crummy.com/software/BeautifulSoup/bs4/doc/ == DATA SCHOOL VIDEOS == Machine learning with scikit-learn: https://www.youtube.com/watch?v=elojMnjn4kk&list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A&index=1 Data analysis with pandas: https://www.youtube.com/watch?v=yzIMircGU5I&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=1 Version control with Git: https://www.youtube.com/watch?v=xKVlZ3wFVKA&list=PL5-da3qGB5IBLMp7LtN8Nc3Efd4hJq0kD&index=1 == SUBSCRIBE FOR MORE VIDEOS == https://www.youtube.com/user/dataschool?sub_confirmation=1 == JOIN THE DATA SCHOOL COMMUNITY == Newsletter: http://www.dataschool.io/subscribe/ Twitter: https://twitter.com/justmarkham Facebook: https://www.facebook.com/DataScienceSchool/
Views: 14418 Data School
Web scraping and parsing with Beautiful Soup & Python Introduction p.1
 
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Welcome to a tutorial on web scraping with Beautiful Soup 4. Beautiful Soup is a Python library aimed at helping programmers https://i9.ytimg.com/vi/aIPqt-OdmS0/0.jpg?sqp=CMTBuMAF&rs=AOn4CLCCdxLaQ0UDTyvhX3N87Txa2iGDZQ&time=1477320913969who are trying to scrape data from websites. To use beautiful soup, you need to install it: $ pip install beautifulsoup4. Beautiful Soup also relies on a parser, the default is lxml. You may already have it, but you should check (open IDLE and attempt to import lxml). If not, do: $ pip install lxml or $ apt-get install python-lxml. To begin, we need HTML. I have created an example page for us to work with: https://pythonprogramming.net/parsememcparseface/ Tutorial code: https://pythonprogramming.net/introduction-scraping-parsing-beautiful-soup-tutorial/ Beautiful Soup 4 documentation: https://www.crummy.com/software/BeautifulSoup/bs4/doc/ https://pythonprogramming.net https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
Views: 155140 sentdex
Python Tutorial: Image Manipulation with Pillow
 
15:48
In this video we will learn how to modify and manipulate images using the Python Pillow Library. Pillow is a fork of the Python Imaging Library (PIL). It will allow us to do many different things to our images such as: changing their file extension, resizing, cropping, changing colors, blurring, and much more. Pillow is extremely useful when you have multiple images you wish to process at once. For example, you can use Pillow to automatically create different sized thumbnails of images you upload to your web server. Let's get started. If you enjoy these videos and would like to support my channel, I would greatly appreciate any assistance through my Patreon account: https://www.patreon.com/coreyms Or a one-time contribution through PayPal: https://goo.gl/649HFY If you would like to see additional ways in which you can support the channel, you can check out my support page: http://coreyms.com/support/ You can find me on: My website - http://coreyms.com/ Facebook - https://www.facebook.com/CoreyMSchafer Twitter - https://twitter.com/CoreyMSchafer Google Plus - https://plus.google.com/+CoreySchafer44/posts Tumblr - https://www.tumblr.com/blog/mycms
Views: 73005 Corey Schafer
Python Machine Learning Tutorial | Machine Learning Algorithms | Python Training | Edureka
 
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( Python Training : https://www.edureka.co/python ) This Edureka Python tutorial (Python Tutorial Blog: https://goo.gl/wd28Zr) gives an introduction to Machine Learning and how to implement machine learning algorithms in Python. Below are the topics covered in this tutorial: 1. Why Machine Learning? 2. What is Machine Learning? 3. Types of Machine Learning 4. Supervised Learning 5. KNN algorithm 6. Unsupervised Learning 7. K-means Clustering Algorithm Check out our playlist for more videos: https://goo.gl/Na1p9G Subscribe to our channel to get video updates. Hit the subscribe button above. #Python #PythonTutorial #PythonMachineLearning #PythonTraining How it Works? 1. This is a 5 Week Instructor led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. For more information, please write back to us at [email protected] Call us at US: 1844 230 6362(toll free) or India: +91-90660 20867 Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Review Sairaam Varadarajan, Data Evangelist at Medtronic, Tempe, Arizona: "I took Big Data and Hadoop / Python course and I am planning to take Apache Mahout thus becoming the "customer of Edureka!". Instructors are knowledge... able and interactive in teaching. The sessions are well structured with a proper content in helping us to dive into Big Data / Python. Most of the online courses are free, edureka charges a minimal amount. Its acceptable for their hard-work in tailoring - All new advanced courses and its specific usage in industry. I am confident that, no other website which have tailored the courses like Edureka. It will help for an immediate take-off in Data Science and Hadoop working."
Views: 114408 edureka!
Data Science Tutorial | Data Science for Beginners | Data Science with Python Tutorial | Simplilearn
 
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This Data Science Tutorial will help you understand what is Data Science, who is a Data Scientist, what does a Data Scientist do and also how Python is used for Data Science. Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. This Data Science tutorial will help you establish your skills at analytical techniques using Python. With this Data Science video, you’ll learn the essential concepts of Data Science with Python programming and also understand how data acquisition, data preparation, data mining, model building & testing, data visualization is done. This Data Science tutorial is ideal for beginners who aspire to become a Data Scientist. This Data Science tutorial will cover the following topics: 1. What is Data Science? ( 00:43 ) 2. Who is a Data Scientist? ( 02:02 ) 3. What does a Data Scientist do? ( 02:25 ) To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the slides here: https://goo.gl/V4Zn8i Read the full article here: https://www.simplilearn.com/career-in-data-science-ultimate-guide-article?utm_campaign=What-is-Data-Science-bTTxei-S1WI&utm_medium=Tutorials&utm_source=youtube Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course. Why learn Data Science? Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. A data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. You can gain in-depth knowledge of Data Science by taking our Data Science with python certification training course. With Simplilearn’s Data Science certification training course, you will prepare for a career as a Data Scientist as you master all the concepts and techniques. Those who complete the course will be able to: 1. Gain an in-depth understanding of data science processes, data wrangling, data exploration, data visualization, hypothesis building, and testing. You will also learn the basics of statistics. Install the required Python environment and other auxiliary tools and libraries 2. Understand the essential concepts of Python programming such as data types, tuples, lists, dicts, basic operators and functions 3. Perform high-level mathematical computing using the NumPy package and its large library of mathematical functions Perform scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO and Weave 4. Perform data analysis and manipulation using data structures and tools provided in the Pandas package 5. Gain expertise in machine learning using the Scikit-Learn package The Data Science with python is recommended for: 1. Analytics professionals who want to work with Python 2. Software professionals looking to get into the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in analytics and data science 5. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=What-is-Data-Science-bTTxei-Data-Sciene-Tutorial-jNeUBWrrRsQ&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn’s courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simp... - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 5967 Simplilearn
Writing a Multistep MapReduce Job Using the mrjob Python Library: From Data Just Right LiveLessons
 
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http://www.informit.com/store/data-just-right-livelessons-video-training-9780133807141 Writing a Multistep MapReduce Job Using the mrjob Python Library is a video sample excerpt from, Data Just Right LiveLessons Video Training -- 7 Hours of Video Instruction Overview Data Just Right LiveLessons provides a practical introduction to solving common data challenges, such as managing massive datasets, visualizing data, building data pipelines and dashboards, and choosing tools for statistical analysis. You will learn how to use many of today's leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery. Data Just Right LiveLessons shows how to address each of today's key Big Data use cases in a cost-effective way by combining technologies in hybrid solutions. You'll find expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis, and more. These videos demonstrate techniques using many of today's leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery. Data Engineer and former Googler Michael Manoochehri provides viewers with an introduction to implementing practical solutions for common data problems. The course does not assume any previous experience in large scale data analytics technology, and includes detailed, practical examples. Skill Level Beginner What You Will Learn Mastering the four guiding principles of Big Data success--and avoiding common pitfalls Emphasizing collaboration and avoiding problems with siloed data Hosting and sharing multi-terabyte datasets efficiently and economically "Building for infinity" to support rapid growth Developing a NoSQL Web app with Redis to collect crowd-sourced data Running distributed queries over massive datasets with Hadoop and Hive Building a data dashboard with Google BigQuery Exploring large datasets with advanced visualization Implementing efficient pipelines for transforming immense amounts of data Automating complex processing with Apache Pig and the Cascading Java library Applying machine learning to classify, recommend, and predict incoming information Using R to perform statistical analysis on massive datasets Building highly efficient analytics workflows with Python and Pandas Establishing sensible purchasing strategies: when to build, buy, or outsource Previewing emerging trends and convergences in scalable data technologies and the evolving role of the "Data Scientist" Who Should Take This Course Professionals who need practical solutions to common data challenges that they can implement with limited resources and time. Course Requirements Basic familiarity with SQL Some experience with a high-level programming language such as Java, JavaScript, Python, R Experience working in a command line environment http://www.informit.com/store/data-just-right-livelessons-video-training-9780133807141
Views: 7511 LiveLessons
Raspberry Pi & Python basic data storage with Tony D! @adafruit #LIVE
 
01:13:39
Live stream to http://twitch.tv/adafruit showing how to store basic data like program state or sensor readings on a Raspberry Pi with Python. Looks at storing and loading data with Python's pickle module, configparser INI files, and CSV format files. Programming note, next week (5/20) there won't be a regular Watch Tony D's Desk video however it will return the week after (5/27). Links mentioned in video: - Code shown in video: https://gist.github.com/tdicola/e0ae6cb64c40f4ab888e90a16114d3b0 - Python standard library reference: https://docs.python.org/3.4/library/ - Python pickle module: https://docs.python.org/3.4/library/pickle.html - PyMOTW pickle description: https://pymotw.com/2/pickle/ - Python configparser module: https://docs.python.org/3.4/library/configparser.html - Python csv module: https://docs.python.org/3.4/library/configparser.html - Google spreadsheets: http://sheets.google.com/ - Python timeit module: https://docs.python.org/2/library/timeit.html Acknowledgements: - Music: bartlebeats - Intro shuttle footage: NASA - Intro fonts: Typodermic - Intro inspiration: Mr. Wizards's World - Matrix background: cool-retro-term & cmatrix ----------------------------------------- Visit the Adafruit shop online - http://www.adafruit.com Subscribe to Adafruit on YouTube: http://adafru.it/subscribe Join our weekly Show & Tell on G+ Hangouts On Air: http://adafru.it/showtell Watch our latest project videos: http://adafru.it/latest New tutorials on the Adafruit Learning System: http://learn.adafruit.com/ Music by bartlebeats: http://soundcloud.com/bartlebeats -----------------------------------------
Views: 5502 Adafruit Industries
Google Analytics Data Mining with R (includes 3 Real Applications)
 
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R is already a Swiss army knife for data analysis largely due its 6000 libraries but until now it lacked an interface to the Google Analytics API. The release of RGoogleAnalytics library solves this problem. What this means is that digital analysts can now fully use the analytical capabilities of R to fully explore their Google Analytics Data. In this webinar, Andy Granowitz, ‎Developer Advocate (Google Analytics) & Kushan Shah, Contributor & maintainer of RGoogleAnalytics Library will show you how to use R for Google Analytics data mining & generate some great insights. Useful Resources:http://bit.ly/r-googleanalytics-resources
Views: 26948 Tatvic
Tweepy installation on Anaconda on Windows OS
 
10:48
This video will show steps to install tweepy on anaconda on windows operating system.
Views: 2331 HowTo
Intro and Getting Stock Price Data - Python Programming for Finance p.1
 
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Welcome to a Python for Finance tutorial series. In this series, we're going to run through the basics of importing financial (stock) data into Python using the Pandas framework. From here, we'll manipulate the data and attempt to come up with some sort of system for investing in companies, apply some machine learning, even some deep learning, and then learn how to back-test a strategy. I assume you know the fundamentals of Python. If you're not sure if that's you, click the fundamentals link, look at some of the topics in the series, and make a judgement call. If at any point you are stuck in this series or confused on a topic or concept, feel free to ask for help and I will do my best to help. https://pythonprogramming.net https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
Views: 186742 sentdex
Python for data science
 
01:00:19
The Python language combines human-friendly syntax, awesome libraries, and computational chops into one of the most powerful languages in the world today. This webinar provides practical tips for how to leverage Python in your data science projects. Mostly this will be specific code tricks and libraries to use, but will also discuss some more general principles (tradeoffs to make, code architecture, etc). To show you how this plays out "in the wild", Field will also do a walk-through of a complete data science project. This talk is geared toward people who have a "hello world" familiarity with Python, but who aren't familiar with it's more advanced tools. See more at: www.thinkbiganalytics.com
Virtual Environment di Python | Python untuk Data Mining Tutorial 4
 
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Python untuk Data Mining | Python for Data Mining Tutorial 4 Data Mining menggunakan bahasa pemrograman Python. Dari Mulai: 1. Alasan Kenapa menggunakan Python 2. Machine Learning Library di Python 3. Komponen bahasa pemrograman Python 4. Virtual environment di Python 5. Dasar-dasar pemrograman Python 6. Numpy, scipy, pandas, matplotlib 7. Data Mining dengan Python 8. Analisis data menggunakan Python 9. Dan sebagainya #Python #DataMining #MachineLearning #DataAnalysis #scikit-learn
Views: 315 Rischan Mafrur
Financial Portfolio Data Analysis with Python | Enthought Software Development
 
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Contact us at [email protected] for more information about our data analysis and visualization software solutions for finance.
Views: 9277 Enthought
Mining Twitter with Python : 2 - Collecting data from Twitter
 
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In order to interact with the Twitter APIs, we need a Python client that implements the different calls to the APIs itself. We will use Tweepy in these tutorials and see how to build our application in multiple parts to collects data from our own Twitter timeline and other users timeline. ----- ------ Channel link: https://goo.gl/nVWDos Subscribe here: https://goo.gl/gMdGUE Link to playlist: https://goo.gl/WIHiEy ---- Join my Facebook Group to stay connected: http://bit.ly/2lZ3FC5 Like my Facebbok Page for updates: https://www.facebook.com/tigerstylecodeacademy/ Follow me on Twitter: https://twitter.com/sukhsingh Profile on LinkedIn: https://www.linkedin.com/in/singhsukh/ ---- Schedule: New educational videos every week ----- ----- Source Code for tutorials on Youtube: http://bit.ly/2nSQSAT ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh ----- Learn Something New: ------ Learn Something New: http://bit.ly/2zSkzGh
Views: 5700 Sukhvinder Singh
Scrape and Parse Wikipedia using Python
 
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Learn how to Scrape data from Wikipedia using Python.
Views: 5415 DevNami
Regular Expressions (Regex) Tutorial: How to Match Any Pattern of Text
 
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In this regular expressions (regex) tutorial, we're going to be learning how to match patterns of text. Regular expressions are extremely useful for matching common patterns of text such as email addresses, phone numbers, URLs, etc. Almost every programming language has a regular expression library, so learning regular expressions with not only help you with finding patterns in your text editors, but also you'll be able to use these programming libraries to search for patterns programmatically as well. Let's get started... The code from this video can be found at: https://github.com/CoreyMSchafer/code_snippets/tree/master/Regular-Expressions Python Regex Tutorial: https://youtu.be/K8L6KVGG-7o If you enjoy these videos and would like to support my channel, I would greatly appreciate any assistance through my Patreon account: https://www.patreon.com/coreyms Or a one-time contribution through PayPal: https://goo.gl/649HFY If you would like to see additional ways in which you can support the channel, you can check out my support page: http://coreyms.com/support/ You can find me on: My website - http://coreyms.com/ Facebook - https://www.facebook.com/CoreyMSchafer Twitter - https://twitter.com/CoreyMSchafer Google Plus - https://plus.google.com/+CoreySchafer44/posts Tumblr - https://www.tumblr.com/blog/mycms
Views: 101350 Corey Schafer