Search results “Ssas data mining vs r”
Introduction to Data Mining in SQL Server Analysis Services
Data mining is one of the key hidden gems inside of Analysis Services but has traditionally had a steep learning curve. In this session, you'll learn how to create a data mining model to predict who is the best customer for you and learn how to use other algorithms to spend your marketing model wisely. You'll also see how to use Time Series analysis for budget and forecast prediction. Finally, you'll learn how to integrate data mining into your application through SSIS or custom coding.
Views: 6855 PASStv
Machine Learning in SQL Server 2016
As a competitive business, turning existing data into actionable predictions is a top priority. Microsoft SQL Server 2016 makes deploying machine learning solutions easier than ever before by enabling consumers to manipulate, transform, and make predictions on their data using custom R scripts. In this video, we show a simple restaurant recommendation engine illuminating the basics of how to write and deploy machine learning solutions in SQL Server 2016. If you have an interest in or are already writing machine learning solutions, SQL Server is a must have! Thanks for checking out our video and feel free to contact us with any questions you might have at [email protected] We love talking about this stuff!
Views: 3873 Northwest Cadence
SSAS Data Mining Overview
Just an overview of SSAS Data Mining. Check out Microsoft's tutorial for more info: https://msdn.microsoft.com/en-us/library/ms167167(v=sql.120).aspx
Views: 1273 Randal Root
SQL Server Analysis Services - SSAS, Data Mining & Analytics : SSAS Deployment
http://ytwizard.com/r/qN5xsS http://ytwizard.com/r/qN5xsS SQL Server Analysis Services - SSAS, Data Mining & Analytics SQL Server, SSAS, MDX, DAX, Data Warehouse, Data Mining, Multi Dimensional Data Modeling, Tabular Model, SSRS, Power BI
Views: 26 Beauty Supply
MSBI - SSAS - Data Mining - Association Rules
MSBI - SSAS - Data Mining - Association Rules
Views: 439 M R Dhandhukia
OLAP and Data Modeling Concepts
This video provides a quick tutorial on OLAP and Multidimensional Data Modeling and illustrates the value that OLAP provides when performing data analysis
Views: 823 eCapital Advisors
What is OLAP?
This video explores some of OLAP's history, and where this solution might be applicable. We also look at situations where OLAP might not be a fit. Additionally, we investigate an alternative/complement called a Relational Dimensional Model. To Talk with a Specialist go to: http://www.intricity.com/intricity101/
Views: 355438 Intricity101
Forecasting with the Microsoft Time Series Data Mining Algorithm
Imagine taking historical stock market data and using data science to more accurately predict future stock values. This is precisely the aim of the Microsoft Time Series data mining algorithm.. MSBI - SSAS - Data Mining - Time Series. In this video you will learn the theory of Time Series Forecasting. You will what is univariate time series analysis, AR, MA, ARMA vesves ARIMA modelling and how to use these models to do forecast.. I am sorry for my poor english. I hope it helps you. when i take the data mining course, i had searched it but i couldnt. So i decided to share this video with you.
Views: 89 Fidela Aretha
Data Mining, Clustering, Visual Studio, SQL Server
Views: 2234 Ben KIM
Predictive Analytics using Analysis Services 2012
Recording from my SQL Saturday Puerto Rico 2013 presentation
Views: 2029 Alan Koo
Olap operations
Olap operations
Views: 16902 IMSUC FLIP
Data Mining - Decision Tree
Use a view to make predictions about bike purchases.
Views: 10804 Mike
Introduction to Data Mining  (1/3)
http://www.creativecommit.com. This video gives a brief demo of the various data mining techniques. The demo mainly uses Microsoft SQL server 2008, BIDS 2008 and Excel for data mining
Views: 149890 creativecommIT
SAS® Enterprise Miner™ Software Demo
http://www.sas.com/enterpriseminer SAS Enterprise Miner streamlines data mining to create accurate predictive and descriptive models based on large volumes of enterprisewide data. SAS ENTERPRISE MINER Reveal valuable insights with powerful data mining software. Descriptive and predictive modeling provide insights that drive better decision making. Now you can streamline the data mining process to develop models quickly. Understand key relationships. And find the patterns that matter most. Looking for benefits? How about: * Build better models with the best tools. * Empower business users. * Improve prediction accuracy. Share reliable results. * Automate model deployment and scoring. LEARN MORE ABOUT SAS ENTERPRISE MINER http://www.sas.com/enterpriseminer SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL http://www.youtube.com/subscription_center?add_user=sassoftware ABOUT SAS SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 75,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world The Power to Know.® VISIT SAS http://www.sas.com CONNECT WITH SAS SAS ► http://www.sas.com SAS Customer Support ► http://support.sas.com SAS Communities ► http://communities.sas.com Facebook ► https://www.facebook.com/SASsoftware Twitter ► https://www.twitter.com/SASsoftware LinkedIn ► http://www.linkedin.com/company/sas Google+ ► https://plus.google.com/+sassoftware Blogs ► http://blogs.sas.com RSS ►http://www.sas.com/rss
Views: 95913 SAS Software
Introduction, Why to learn SSAS and MDX, What you'll need
http://ytwizard.com/r/qN5xsS http://ytwizard.com/r/qN5xsS SQL Server Analysis Services - SSAS, Data Mining & Analytics SQL Server, SSAS, MDX, DAX, Data Warehouse, Data Mining, Multi Dimensional Data Modeling, Tabular Model, SSRS, Power BI
Views: 8 Beauty Supply
Predictive Modelling Techniques | Data Science With R Tutorial
This lesson will teach you Predictive analytics and Predictive Modelling Techniques. Watch the New Upgraded Video: https://www.youtube.com/watch?v=DtOYBxi4AIE After completing this lesson you will be able to: 1. Understand regression analysis and types of regression models 2. Know and Build a simple linear regression model 3. Understand and develop a logical regression 4. Learn cluster analysis, types and methods to form clusters 5. Know more series and its components 6. Decompose seasonal time series 7. Understand different exponential smoothing methods 8. Know the advantages and disadvantages of exponential smoothing 9. Understand the concepts of white noise and correlogram 10. Apply different time series analysis like Box Jenkins, AR, MA, ARMA etc 11. Understand all the analysis techniques with case studies Regression Analysis: • Regression analysis mainly focuses on finding a relationship between a dependent variable and one or more independent variables. • It predicts the value of a dependent variable based on one or more independent variables • Coefficient explains the impact of changes in an independent variable on the dependent variable. • Widely used in prediction and forecasting Data Science with R Language Certification Training: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-r-tools-training?utm_campaign=Predictive-Analytics-0gf5iLTbiQM&utm_medium=SC&utm_source=youtube #datascience #datasciencetutorial #datascienceforbeginners #datasciencewithr #datasciencetutorialforbeginners #datasciencecourse The Data Science with R training course has been designed to impart an in-depth knowledge of the various data analytics techniques which can be performed using R. The course is packed with real-life projects, case studies, and includes R CloudLabs for practice. Mastering R language: The course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. Mastering advanced statistical concepts: The course also includes the various statistical concepts like linear and logistic regression, cluster analysis, and forecasting. You will also learn hypothesis testing. As a part of the course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and Internet. R CloudLab has been provided to ensure a practical and hands-on experience. Additionally, we have four more projects for further practice. Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 199787 Simplilearn
Data Mining using the Excel Data Mining Addin
The Excel Data Mining Addin can be used to build predictive models such as Decisions Trees within Excel. The Excel Data Mining Addin sends data to SQL Server Analysis Services (SSAS) where the models are built. The completed model is then rendered within Excel. I also have a comprehensive 60 minute T-SQL course available at Udemy : https://www.udemy.com/t-sql-for-data-analysts/?couponCode=ANALYTICS50%25OFF
Views: 72362 Steve Fox
Data mining algorithms with SQL Server and R: part 2 - Dejan Sarka
Breakout session from DevWeek 2015 http://devweek.com/ DevWeek is the UK’s leading conference for professional software developers, architects and analysts. With insights on the latest technologies, best practice and frameworks from industry-leading experts, plus hands-on workshop sessions, DevWeek is your chance to sharpen your skills - and ensure every member of your team is up to date. Please visit http://devweek.com/ for information on the latest event. ----------------------------------------­----------------------------------------­----- DevWeek is part of DevWeek Events, a series of software development conferences and workshops, including DevWeek's sister conference 'Software Architect' (http://software-architect.co.uk/), brought to you by Publicis UK. ----------------------------------------­----------------------------------------­-----
Views: 104 DevWeek Events
Forecast the Price of Gold with Excel and SQL Server - Data Mining Tutorial
Learn about data mining with SQL Server 2012 Analysis Services and Excel 2013, using historical gold pricing data, to predict future prices. To follow this tutorial, you should have SSAS and the Data Mining Add-in for Excel.
Views: 6194 Edward Kench
Prediction and Classification with Decision Tree
This vlog introduces you to decision tree in R and how categorical data can be classified and predicted by this algorithm.
Views: 1411 Keshav Singh
R Tools for Visual Studio – Predictive Analytics for C# applications
Microsoft recently announced R Tools for Visual Studio. This free product from Microsoft turns Visual Studio into a powerful R development environment. R is a software environment that is an alternative to SAS and SPSS for statistical analysis and modelling. R is excellent for building predictive models and offers support for a vast number of such models. Syncfusion offers the ability to take predictive models trained using R and run them inside a .NET environment with no dependency on the R environment. The product is called Syncfusion Essential Predictive Analytics. This video walks through a regression sample from model training using R inside Visual Studio to deployment inside a C# application using Syncfusion Essential Predictive Analytics library. Links R Tools for Visual Studio - https://www.visualstudio.com/en-us/features/rtvs-vs.aspx Free eBook on R published by Syncfusion - https://www.syncfusion.com/resources/techportal/ebooks/rsuccinctly Learn more and download a free trial of Predictive Analytics for C# today: http://bit.ly/2HbvApi
Views: 12342 Syncfusion, Inc
Microsoft Visual Studio - Business Intelligence Data Mining
For more videos visit http://computerseekho.com http://www.facebook.com/pages/ComputerSeekhocom/205208676168940
Views: 19109 Mayank Malik
Statistical Aspects of Data Mining (Stats 202) Day 10
Google Tech Talks July 31, 2007 ABSTRACT This is the Google campus version of Stats 202 which is being taught at Stanford this summer. I will follow the material from the Stanford class very closely. That material can be found at www.stats202.com. The main topics are exploring and visualizing data, association analysis, classification, and clustering. The textbook is Introduction to Data Mining by Tan, Steinbach and Kumar. Googlers are welcome to attend any classes which they think might be of interest to them. Credits: Speaker:David Mease
Views: 18271 GoogleTechTalks
Business Intelligence Solution Components Overview
http://ytwizard.com/r/qN5xsS http://ytwizard.com/r/qN5xsS SQL Server Analysis Services - SSAS, Data Mining & Analytics SQL Server, SSAS, MDX, DAX, Data Warehouse, Data Mining, Multi Dimensional Data Modeling, Tabular Model, SSRS, Power BI
Views: 12 Beauty Supply
Analysis Services tutorial. Creating OLAP cube. Introduction to data warehouse
Analysis Services is a collection of OLAP supplied in Microsoft SQL Server. See more lessons http://www.learn-with-video-tutorials.com/analysis-services-video-tutorial
Walkthrough: Analysis Services live report in Power BI
I walk through how to create and publish a report that uses a live connection to Analysis Services. This starts with Power BI Desktop, and makes use of the enterprise gateway once the report is published. SUBSCRIBE! https://www.youtube.com/channel/UCFp1vaKzpfvoGai0vE5VJ0w?sub_confirmation=1 LET'S CONNECT! Guy in a Cube -- http://twitter.com/guyinacube -- http://www.facebook.com/guyinacube -- http://aka.ms/guyinacube (YouTube) -- https://beme.com/guyinacube -- Snapchat - guyinacube -- https://www.instagram.com/guyinacube/ Adam Saxton (Microsoft Employee) -- http://twitter.com/awsaxton -- https://www.facebook.com/asaxton
Views: 31990 Guy in a Cube
Why Predictive Model: in 9 Minutes
A non-analytical business introduction to predictive modeling. http://www.bostondecision.com.
Views: 29031 Timothy DAuria
Rearchitecting a SQL Database for Time-Series Data | DataEngConf NYC '17
Don’t miss the next DataEngConf in Barcelona: https://dataeng.co/2O0ZUq7 ABOUT THE TALK: Today everything is instrumented, generating more and more time-series data streams that need to be monitored and analyzed. When it comes to storing this data, many developers start with some well-trusted system like PostgreSQL. But when their data hits a certain scale, they often give up its query power and ecosystem by migrating to some NoSQL or other "modern" time-series architecture. In this talk, I describe why this perceived trade-off isn't necessary, and how we've built an efficient, scalable time-series database engineered up from PostgreSQL. In particular, the nature of time-series workloads one finds in devops, monitoring, IoT, finance, and elsewhere -- inserting new data about recent events -- presents very different demands than general transactional (OLTP) workloads. We've architected our time-series database to take advantage of and embrace these differences. The system architecture automatically partitions data across both time and space, even though it exposes the illusion of a single continuous table -- a hypertable -- across all of your data spread across one or many servers. Its distributed query optimizations both hide the fact that users are interacting with many "chunks" of data, which are right-sized by volume and time constraints, and minimize which and how chunks are accessed to answer queries. In fact, the database supports "full SQL" against this hypertable (e.g., secondary indexes, rich query predicates and group bys, aggregations, windowing functions, upserts, CTEs, JOINs). Through performance benchmarks, I show how the database scales much better than PostgreSQL, even on a single node. In particular, it avoids the "performance cliff" that vanilla PostgreSQL experiences at 10s of millions of rows, while maintaining robust performance past 100B rows. The database is implemented as a PostgreSQL extension, released under the Apache 2 license. ABOUT THE SPEAKER: Michael J. Freedman is a Professor in the Computer Science Department at Princeton University, as well as the co-founder and CTO of Timescale, building an open-source database that scales out SQL for time-series data. His work broadly focuses on distributed systems, networking, and security, and has led to commercial products and deployed systems reaching millions of users daily. Honors include a Presidential Early Career Award (PECASE), SIGCOMM Test of Time Award, Sloan Fellowship, DARPA CSSG membership, and multiple award publications. Follow DataEngConf on: Twitter: https://twitter.com/dataengconf LinkedIn: https://www.linkedin.com/company/hakkalabs/ Facebook: https://web.facebook.com/hakkalabs
Views: 870 Hakka Labs
Load Data FROM SSAS CUBE to Table via SSIS - 22
https://www.youtube.com/user/masterkeshav This vlog demonstrate a simple effective way to download CUBE data into a relational Table using SSIS.
Views: 9949 Keshav Singh
The Analysis services for Adventure Works Cycles
Build the data mining model structure and built the decision tree with proper decision nodes
Views: 73 ACUMEN
Uncharted Lecture Series: "A Framework for Data Mining in Wind Power Time Series"
On Thursday, March 19, 2015, Oliver Kramer, a juniorprofessor for computational intelligence at the University of Oldenburg in Germany and an ICSI alumnus, gave a talk about his work on data mining and green energy. Dr. Kramer's full abstract and bio are available at https://www.icsi.berkeley.edu/icsi/events/2015/03/kramer-data-mining-framework Abstract: Wind energy is playing an increasingly important part for ecologically friendly power supply. The fast growing infrastructure of wind turbines can be seen as a large sensor system that screens the wind energy at a high temporal and spatial resolution. The resulting databases consist of huge amounts of wind energy time series data that can be used for prediction, controlling, and planning purposes. In this talk, I describe WindML, a Python-based framework for wind energy related machine learning approaches. Read the full abstract at https://www.icsi.berkeley.edu/icsi/events/2015/03/kramer-data-mining-framework
Views: 584 ICSIatBerkeley
Basic Data Mining
A Guide to ShareScope's Data Mining (stock-screening) facility
Views: 2336 ShareScope | SharePad
Sales Forecasting with Excel and the SQL Server 2012 Data Mining Add-in Tutorial
Use the Excel Data Mining add-in for SQL 2012 Analysis Services. See how simple it is to build a predictive model that forecasts sales or other values based on historical data.
Views: 12465 Edward Kench
Data Science Tutorial | Data Science Trainign | Understanding Data science
In this session presented by a Data scientist, he covers data science from the basics. The key topics covered in this webinar are: a) What is Data science b) Data mining/Analytics Vs Data Science c) Data Science Projects Framework d) Popular techniques To know more about Data Science course with R (http://bit.ly/2yvsgR5) and Big data analytics course (http://bit.ly/2AziAFY). Techcanvass is a software development and training organization. We provide IT certifications training for mid-level professionals. We specialize in the following areas: a) Selenium v3.0 training (CP-SAT and Techcanvass Certification) b) IIBA Business Analysis certifications (all levels) c) Certified Agile Business Analyst Training d) Data Science Training ( R, Python and Big Data) Website: http://techcanvass.com Facebook Page: https://www.facebbook.com/Techcanvass Twitter Handle: @techcanvass
Views: 215 Techcanvass
Usage of R in SQL Server for better data understanding
Language R for Statistical computing is powerful language for data analysis with all great features for data import from SQL environment. Using R with SQL server data will help data scientists and data analysts prepare, explore and validate data much easier, as well as to use wide range of statistics; from univariate to multivariate. Session will focus mainly on: 1) on connecting R Language with SQL server using standard ODBC connectors and T-SQL procedures. 2) how to validate data with using classical statistical methods on SQL transactional data. 3) how to use R output in SSRS and bring extra information to reports. Tomaž Kaštrun Tomaž Kaštrun is BI developer who focuses mainly on data mining, data quality and programming in SQL and .NET. He has been working with SQL Server since version 2000. Recorded on 13 May 2014 at PASS Data Warehousing and Business Intelligence Virtual Chapter (PASS DW/BI VC) Join PASS DW/BI Virtual Chapter at http://bi.sqlpass.org Follow us on Twitter @PASSBIVC
how to draw star schema slowflake schema and fact constelation in hindi
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing For full course:https://goo.gl/bYbuZ2 More videos coming soon so Subscribe karke rakho  :  https://goo.gl/85HQGm for full notes   please fill the form for notes :https://goo.gl/forms/MJD1mAOaTzyag64P2 For full hand made  notes of data warehouse and data mining  its only 200 rs payment options is PAYTM :7038604912 once we get payment notification we will mail you the notes on your email id contact us at :[email protected] For full course :https://goo.gl/Y1UcLd Topic wise: Introduction to Datawarehouse:https://goo.gl/7BnSFo Meta data in 5 mins :https://goo.gl/7aectS Datamart in datawarehouse :https://goo.gl/rzE7SJ Architecture of datawarehouse:https://goo.gl/DngTu7 how to draw star schema slowflake schema and fact constelation:https://goo.gl/94HsDT what is Olap operation :https://goo.gl/RYQEuN OLAP vs OLTP:https://goo.gl/hYL2kd decision tree with solved example:https://goo.gl/nNTFJ3 K mean clustering algorithm:https://goo.gl/9gGGu5 Introduction to data mining and architecture:https://goo.gl/8dUADv Naive bayes classifier:https://goo.gl/jVUNyc Apriori Algorithm:https://goo.gl/eY6Kbx Agglomerative clustering algorithmn:https://goo.gl/8ktMss KDD in data mining :https://goo.gl/K2vvuJ ETL process:https://goo.gl/bKnac9 FP TREE Algorithm:https://goo.gl/W24ZRF Decision tree:https://goo.gl/o3xHgo more videos coming soon so channel ko subscribe karke rakho
Views: 77146 Last moment tuitions
Clustering data (and machine learning) (3-3b)
This video is part of the Analyzing and Visualizing Data with Power BI course available on EdX.  To sign up for the course, visit: http://aka.ms/pbicourse. To read more: Power BI service https://aka.ms/pbis_gs Power BI Desktop https://aka.ms/pbid_gs Power BI basic concepts tutorial: https://aka.ms/power-bi-tutorial To submit questions and comments about Power BI, please visit community.powerbi.com. To submit questions and comments about Power BI, please visit community.powerbi.com.
Views: 18705 Microsoft Power BI
.NET to The Power of R(1) - TJ Gokcen
R is a language for statistical programming that is widely used among data scientists. Last year Microsoft purchased Revolution Analytics, a leading R company. As a result, Microsoft recently released Visual Studio Tools for R and announced that R is going to be included in the upcoming SQL Server 2016. In this session, we will take a look at R from an introductory point of view and see how the power of R can be used by .net developers. Some of the highlights are: - What is R and why does it matter? - A brief look into statistics - R in a nutshell - “There is no R in Develop, but there is one in DevelopeR”. R Basics. - Power of R: some basic examples showcasing R - A brief look at R in SQL Server 2016 - Building a dashboard with asp.net MVC and R (getting data from SQL Server as well as the internet) NDC Conferences https://ndcsydney.com https://ndcconferences.com
Views: 240 NDC Conferences
Forecasting using Regression Analysis in Microsoft OLAP Cubes
Building a linear regression calculation using MDX in a Microsoft Analysis Services OLAP cube, and extending the results into the future for the purpose of multidimensional forecasting can leverage vast amounts of data to analyze the past and predict the future with agility, flexibility, and scalability. Today I will walk you through an example of how linear regression and forecasting analyses can be built using simple MDX within a traditional Kimball-style star schema. The following link provides more details about the methodology: http://blog.gnetgroup.com/bi/2013/03/28/forecasting-mdx-linear-regression-ssas-olap-cube/
Views: 5368 Nihilent Technologies
Data Modeling for Power BI
A data model is like the foundation for your house, get it right and everything else goes better. Join the Power BI desktop team in this session to learn about the key steps, and best practices, you need to take to ensure a good data model.
Views: 70241 Microsoft Power BI
SQL Server 2017 Features
A comprehensive review of SQL Server development, reporting, analytic, and data warehouse features as of SQL Server 2017.
Views: 129 Bryan Cafferky
Visual Studio for Machine Learning
Whether it is building a model for online product recommendation, or developing a project using Microsoft SQL Server 2016 with R, where you need to develop both the models, and the stored procedure, Visual Studio enables both developers and data scientists to work together to build your next generation intelligent apps and services. All the tooling you need to analyze, build models, and create smart apps, including: Python Tools for Visual Studio and R Tools for Visual Studio. Join us in this this session, as we show you how Visual Studio can be used to do data science, and help you create the next intelligent application!
SQL Server Analysis Services 2014: табличная модель
SQL Server Analysis Services 2014: табличная модель - альтернатива кубам?
Modelling and Data Mining
This Lecture talks about Modelling and Data Mining
Views: 710 Cec Ugc
Data Mining Classification Task with Weka and RapidMiner Tools.
Data Mining Classification Task with Weka and RapidMiner Tools. *WATCH IN HD TO GET BETTER QUALITY* In this video we will show a tutorial on how to do classification task using Weka and RapidMiner tools. Weka - http://www.cs.waikato.ac.nz/ml/weka/ RapidMiner - https://rapidminer.com/ SSK4604 - Data Mining University Putra Malaysia
Views: 1365 Toffy
Machine Learning Tutorial 17 - Using Models for New Data
Machine Learning and Predictive Analytics. #MachineLearning Learn More: http://amzn.to/2Ds5iML (Fundamentals Of Machine Learning for Predictive Data Analytics). This online course covers big data analytics stages using machine learning and predictive analytics. Big data and predictive analytics is one of the most popular applications of machine learning and is foundational to getting deeper insights from data. Starting off, this course will cover machine learning algorithms, supervised learning, data planning, data cleaning, data visualization, models, and more. This self paced series is perfect if you are pursuing an online computer science degree, online data science degree, online artificial intelligence degree, or if you just want to get more machine learning experience. Enjoy! Check out the entire series here: https://www.youtube.com/playlist?list=PL_c9BZzLwBRIPaKlO5huuWQdcM3iYqF2w&playnext=1 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Support me! http://www.patreon.com/calebcurry Subscribe to my newsletter: http://bit.ly/JoinCCNewsletter Donate!: http://bit.ly/DonateCTVM2. ~~~~~~~~~~~~~~~Additional Links~~~~~~~~~~~~~~~ More content: http://CalebCurry.com Facebook: http://www.facebook.com/CalebTheVideoMaker Google+: https://plus.google.com/+CalebTheVideoMaker2 Twitter: http://twitter.com/calebCurry Amazing Web Hosting - http://bit.ly/ccbluehost (The best web hosting for a cheap price!)
Views: 604 Caleb Curry
Basket Analysis using BI Office and SSAS Tabular
Ian MacDonald from Pyramid Analytics gives a demo on Basket Analyses using BI Office and SSAS Tabular. Use BI Office to easily build an ad-hoc Analysis Services Tabular Edition analytic data set and perform associative analysis using the unique features of BI Office. For comments, discussions, and additional BI Office information, visit our user community at https://community.pyramidanalytics.com/!
Views: 544 Pyramid Analytics
Dashboard, Data Mining & Reports
A quick overview of reporting and data options
Views: 241 Kristina Simkins
Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data
Author: David Hallac, Department of Electrical Engineering, Stanford University Abstract: Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. More on http://www.kdd.org/kdd2017/ KDD2017 Conference is published on http://videolectures.net/
Views: 824 KDD2017 video