Home
Search results “Spatial data mining course notes”
Introduction to data mining and architecture  in hindi
 
09:51
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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 200rs 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: 126654 Last moment tuitions
INTRODUCTION TO DATA MINING IN HINDI
 
15:39
find relevant notes at-https://viden.io/
Views: 96234 LearnEveryone
DBSCAN ( Density Based Spatial  Clustering of Application with Noise )  in Hindi | DWM | Data Mining
 
03:22
Sample Notes : https://drive.google.com/file/d/19xmu... for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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 200rs 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: 7317 Last moment tuitions
KDD ( knowledge data discovery )  in data mining in hindi
 
08:50
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 45577 Last moment tuitions
Getting Started with Spatial Data Analysis in R
 
49:31
Spatial and spatial-temporal data have become pervasive nowadays. We are constantly generating spatial data from route planners, sensors, mobile devices, and computers in different fields like Transportation, Agriculture, Social Media. These data need to be analyzed to generate hidden insights that can improve business processes, help fight crime in cities, and much more. Simply creating static maps from these data is not enough. In this webinar we shall look at techniques of importing and exporting spatial data into R; understanding the foundation classes for spatial data; manipulation of spatial data; and techniques for spatial visualization. This webinar is meant to give you introductory knowledge of spatial data analysis in R needed to understand more complex spatial data modeling techniques. In this webinar, we will cover the following topics: -Why use R for spatial analysis -Packages for spatial data analysis -Types of spatial data -Classes and methods in R for spatial data analysis -Importing and exporting spatial data -Visualizing spatial data in R
Views: 38568 Domino Data Lab
Spatial Query and Analysis in GIS in HINDI
 
10:46
Notes of Spatial Query and Analysis in GIS in this link - https://viden.io/knowledge/spatial-query-analysis-gis?utm_campaign=creator_campaign&utm_medium=referral&utm_source=youtube&utm_term=ajaze-khan-1
Views: 1635 LearnEveryone
Spatial interpolation techniques
 
51:52
Spatial Interpolation techniques
Spatial Data Science con R (English subtitles)
 
56:06
Todos los materiales de la presentación incluyendo el código fuente y los datos de muestra se pueden descargar desde este link: http://amsantac.co/blog/es/2016/08/07/spatial-data-science-r-es.html All the English-translated materials for this webinar, including source code and sample data, can be downloaded from this link: http://amsantac.co/blog/en/2016/08/07/spatial-data-science-r.html En este webinar se explican algunos conceptos y herramientas de Spatial Data Science, con un énfasis en el uso del lenguaje R durante las diferentes fases de trabajo, desde la importación y procesamiento de datos espaciales hasta la visualización y publicación de resultados. No olvides suscribirte a mi canal de Youtube para más videos! In this webinar I talked about Data Science in the context of its application to spatial data and explained how we can use the R language for the analysis of geographic information within the different stages of a data science workflow, from the import and processing of spatial data to visualization and publication of results. Subscribe to my channel on Youtube for more videos!
Views: 2515 Alí Santacruz
Introduction to Datawarehouse in hindi
 
10:36
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 190983 Last moment tuitions
Concept Hierarchies - Georgia Tech - KBAI: Part 2
 
03:12
Watch on Udacity: https://www.udacity.com/course/viewer#!/c-ud409/l-1649018590/m-1659588547 Check out the full Advanced Operating Systems course for free at: https://www.udacity.com/course/ud409 Georgia Tech online Master's program: https://www.udacity.com/georgia-tech
Views: 3824 Udacity
Data Mining, Classification, Clustering, Association Rules, Regression, Deviation
 
05:01
Complete set of Video Lessons and Notes available only at http://www.studyyaar.com/index.php/module/20-data-warehousing-and-mining Data Mining, Classification, Clustering, Association Rules, Sequential Pattern Discovery, Regression, Deviation http://www.studyyaar.com/index.php/module-video/watch/53-data-mining
Views: 79133 StudyYaar.com
Lecture - 34 Data Mining and Knowledge Discovery
 
54:46
Lecture Series on Database Management System by Dr. S. Srinath,IIIT Bangalore. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 132116 nptelhrd
Gestalt Principles and Visualization Process -- Introduction to Data Visualization 1.3
 
17:20
March 29th, Lecture on Visual Encodings (Part 3) References: https://emeeks.github.io/gestaltdataviz/section1.html http://benfry.com/phd/ Lecture notes and slides: http://jay-oh-en.github.io/courses/usf-datavis/2016/introduction-to-the-course.html Course Webpage: http://jay-oh-en.github.io/courses/usf-datavis/ Live Stream: https://www.youtube.com/channel/UCi0Hd3U6xb4V0ApUhAIfu9Q/live Contact: https://twitter.com/clearspandex Previous video: https://youtu.be/vOA5NByewLc Next video: https://youtu.be/LCK3YzcUhA0 --- Recordings from the University of San Francisco's Spring 2016 MSAN 622 course: Introduction to Data and Information Visualization (taught by Jonathan Dinu). If you are not in the class, I still invite you participate by submitting your own comments/questions (about data visualization) or by adding your perspective to the discussions! This live stream will broadcast class lectures on: * Tuesday ~3-4pm PST * Thursday ~1-2pm PST Archival videos will be post-processed after the lecture and posted here
Views: 148 Jonathan Dinu
Anomaly Detection: Algorithms, Explanations, Applications
 
01:26:56
Anomaly detection is important for data cleaning, cybersecurity, and robust AI systems. This talk will review recent work in our group on (a) benchmarking existing algorithms, (b) developing a theoretical understanding of their behavior, (c) explaining anomaly "alarms" to a data analyst, and (d) interactively re-ranking candidate anomalies in response to analyst feedback. Then the talk will describe two applications: (a) detecting and diagnosing sensor failures in weather networks and (b) open category detection in supervised learning. See more at https://www.microsoft.com/en-us/research/video/anomaly-detection-algorithms-explanations-applications/
Views: 4528 Microsoft Research
Geostatistics Basics
 
29:51
Lecture by Luc Anselin on point pattern analysis (2006)
Views: 8700 GeoDa Software
Data Preprocessing in Hindi |DMBI | Data Warehouse and Data mining Tutorials
 
05:28
Sample Notes : https://drive.google.com/file/d/19xmu... for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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 200rs 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: 5765 Last moment tuitions
what is  Olap operation in hindi
 
08:07
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 118139 Last moment tuitions
Decision tree with solved example in hindi (ID3 algorithm) | Artificial intelligence series
 
23:28
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 99456 Last moment tuitions
Sampling: Simple Random, Convenience, systematic, cluster, stratified - Statistics Help
 
04:54
This video describes five common methods of sampling in data collection. Each has a helpful diagrammatic representation. You might like to read my blog: https://creativemaths.net/blog/
Views: 616953 Dr Nic's Maths and Stats
GPS to GIS: Post-Field Data Collection Considerations
 
02:50
This series of videos describes how to use GPS and GIS in educational instruction--specifically, the whys and hows of gathering field data such as historical buildings, trees, pH in streams, invasive species, social zones on campus, and so on--and then mapping those data to analyze their spatial pattern and assess the issue from a spatial perspective. This video considers such important issues as deciding how and what to collect, GPS satellite reception, thinking like a database, and other considerations.
Views: 162 ESRIEdTeam
Data Mining  Association Rule - Basic Concepts
 
06:53
short introduction on Association Rule with definition & Example, are explained. Association rules are if/then statements used to find relationship between unrelated data in information repository or relational database. Parts of Association rule is explained with 2 measurements support and confidence. types of association rule such as single dimensional Association Rule,Multi dimensional Association rules and Hybrid Association rules are explained with Examples. Names of Association rule algorithm and fields where association rule is used is also mentioned.
11. Introduction to Machine Learning
 
51:31
MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: http://ocw.mit.edu/6-0002F16 Instructor: Eric Grimson In this lecture, Prof. Grimson introduces machine learning and shows examples of supervised learning using feature vectors. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 305694 MIT OpenCourseWare
K Medoid with Sovled Example in Hindi | Clustering | Datawarehouse and Data mining series
 
20:47
In this video we have solve the sum of K medoid which is used in clustering it is an advance version of K mean Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 26880 Last moment tuitions
Open Science: RKWard Overview
 
13:31
Note: The artifacting was due to flipping being enabled on my video driver. A very brief overview of RKWard; a transparent front-end (GUI & IDE) for the R programming language. http://en.wikipedia.org/wiki/R_(programming_language) http://en.wikipedia.org/wiki/Rkward http://rkward.sourceforge.net/
Views: 3384 hyperscientist
how to draw star schema slowflake schema and fact constelation in hindi
 
09:41
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: 70407 Last moment tuitions
Apriori Algorithm with solved example|Find frequent item set in hindi | DWM | ML | BDA
 
11:36
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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 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: 113335 Last moment tuitions
Senior Loeb Scholar lecture: David Harvey
 
01:48:04
3/28/16 It is David Harvey’s contention that the production of space, especially the distribution and organization of the territory, constitutes a principal aspect of capitalist economies. His writings on this theme have contributed to the ongoing political debate on globalization and on the different spatial strategies associated to global processes. A foundation of Harvey’s intellectual project is his “close reading” and interpretation of Karl Marx’s Capital, which he has taught and read for decades and documented in his Companion to Marx’s Capital (2010). But Harvey’s work is distinguished by the way he has brought Marxism together with geography with productive results for each discipline. For instance, he has approached the overaccumulation of capital by way of its reflection in spatial expansion in order to demonstrate its causative role. His book Limits to Capital (1982), which traces this argument, is a mainstay of the contemporary understanding of capitalism’s perennial economic crises (among others are Ernest Mandel’s Late Capitalism (1972), Giovanni Arrighi’s Long 20th Century (1994) and Robert Brenner’s Economics of Global Turbulence (2006)). Among other ideas, Harvey is known for his critical interpretation of the ideas of Henri Lefebvre and his own formulation of the “right to the city.” His book Spaces of Hope (2000) explores a role for architecture in bridging between the human body and the uneven development that is characteristic of globalization. Asked to single out a favorite of Harvey’s books, Dean Mohsen Mostafavi refers to Harvey’s book Social Justice and the City (1973) as “an important articulation of the relationship between the city as a physical artifact and its social consequences. His writings have provided an acute analysis of our society and provide an indispensable framework for new forms of spatial imagination." David Harvey, Distinguished Professor of Anthropology & Geography at the Graduate Center of the City University of New York (CUNY), is the 2015–2016 Senior Loeb Scholar.
Views: 23771 Harvard GSD
OLAP vs OLTP in hindi
 
07:32
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 80227 Last moment tuitions
Agglomerative clustering  algorithmn with example |data mining lectures|machine learning
 
13:31
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 66547 Last moment tuitions
Naive Bayes Classifier with Solved Example|Type 1| DWM | ML | BDA
 
17:59
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 97143 Last moment tuitions
Naive Bayes Classifier with Solved Example|Type 1| DWM | ML | BDA
 
24:22
In this video we have explain the basic concept of Naive Bayes and some concept of condition probability and solved an Example of Naive bayes in which we try to find out the prediction and its also help in classification Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 25148 Last moment tuitions
Cycling - Space-time analysis
 
17:57
Here Godwin Yeboah and Seraphim Alvanides from the University of Northumbria present their work on the space-time analysis of urban cyclists. The data is collected from GPS devices that participants took with them for the duration of the study (1 week). It was filmed at the 2012 RGS conference in Edinburgh
Views: 151 Robin Lovelace
FP TREE Algorithm with solved example|Find frequent item set in hindi (data mining)
 
14:35
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 60529 Last moment tuitions
Machine learning - Decision trees
 
01:06:06
Decision trees for classification. Slides available at: http://www.cs.ubc.ca/~nando/540-2013/lectures.html Course taught in 2013 at UBC by Nando de Freitas
Views: 169064 Nando de Freitas
M.Tech (CS) Thesis Work—Prj. Recommender System
 
38:13
Thesis work Title: A Novel Framework For Recommendations Based On Analyzing Sentiments From Textual Reviews Author: Abhishek kumar Course: M.Tech (CSE) University: PTU College: CGC-COE, Landran, Mohali (PB) Month/Year of Submission: Sept. 2017 ABSTRACT: From the beginning of 1990s, Recommender systems have been an integral part of Research to overcome information overload issue. Recommender Systems are everywhere, from E-Commerce websites to Academic Research. Every person is having unique taste and preferences for the objects(living/non-living) they interact with. Based on that taste and preferences what might be the similar objects user might find interesting and might be recommended to him/her. If person enjoys reading web development books, then based on his/her preferences what might be other good web development books, he/she might like if recommended. There are various approaches for the design of Recommender system; and Sentimental Analysis is among one of them. For most of Sentiment Analysis based Recommender Systems’ the core of whole model relates closely with the Rating Prediction Task. The whole Recommender System depends on computed/predicted ratings directly or indirectly. In this thesis work, NRPS Model was proposed. NRPS is a Rating prediction system, which predicts the Ratings by mining the sentimental information from social users’ reviews. For experiments, a real-world dataset was chosen from Yelp(ii). From the users’ generated reviews, product features were extracted via LDA algorithm and Sentimental dictionaries were constructed for the computation of ratings scores. ANN was used for reviews’ ratings scores prediction. The proposed model was implemented via 3 technologies MatLab(iii), Java(iv) and PHP(v). Proposed Rating Prediction model has been compared with RPS[1] and SVMRPS[2] Models. For performance analysis, two performance evaluation metrics—RMSE and MAE were used. Experimental Results shows the significant improvement over the RPS [1] and SVMRPS[2] Models, over a real world dataset. ACKNOWLEDGMENTS I would like to thank Dr. Manish Mahajan (HOD, CGC-COE), both of my guides Mr. Ranjeet Singh and Ms. Deepika Sood; CGC College of Engineering, Landran, Coordinator, for their kind support.I also owe my sincerest gratitude towards Ms. Dapinder Kaur (Class Coordinator), Department of CSE CGC-COE Landran, Mohali for her pearls of wisdom, during the course of this research. I also owe a gratitude towards my classmates especially Neeraj Baatish, Harpreet Kaur, faculty members (CGC-COE, CSE Department)—Mr. Jagbir Singh Gill, Mr. Gaurav Goel and Mr. Tejpal Prasher; for their guidance and support during my M.Tech course. END-NOTES: i https://en.wikipedia.org/wiki/Web_2.0 ii https://www.yelp.com iii https://en.wikipedia.org/wiki/MATLAB iv https://en.wikipedia.org/wiki/Java_(programming_language) v https://en.wikipedia.org/wiki/PHP REFERENCES: [1] X. Lei, X. Qian, and G. Zhao, “Rating Prediction Based on Social Sentiment from Textual Reviews,” IEEE Trans. Multimed., vol. 18, no. 9, pp. 1910–1921, 2016. [2] A. Kumar, R. Singh, and R. Saini, “SVMRPS — Support Vector Machine based Rating Prediction System,” 2017.
Views: 89 Alex21c
Data Mining Lecture -- Decision Tree | Solved Example (Eng-Hindi)
 
29:13
-~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 125737 Well Academy
Point Clustering in ArcGIS Online
 
01:02
Learn how to get started with point clustering in ArcGIS Online with this short tutorial. What is clustering? If your map has a layer with a large number of points, you can configure clustering to make it easier to visually extract meaningful information from your data. When you enable clustering, Map Viewer groups point features that are within a certain distance of one another on screen into one symbol.
Views: 1287 Lisa Berry
What Is A Multimedia Database?
 
00:46
The extension of multimedia database systems. Googleusercontent search. Traditional databases contained 11 mar 2016 a multimedia database is that hosts one or more primary media file types such as. Multimedia is a combination of text, graphics, animations, audio and video converted from different formats into digital media. Characteristics of mdbmsdata types. A multimedia database (mmdb) is a collection of related data. Operations on data abstract. Mp3 17 sep 2008 organizationmm database system architecturemm service modelmultimedia data storage 19 dec 2012wei tsang ooimmdbms querying interface, indexing anda that is dedicated to the storage, management, and access of one or more media types, such as text, image, video, sound, diagram, etc from publisher multimedia management systems presents issues techniques used in building 10. Text audio graphic video animationmultimedia data typically means digital images, audio, video, animation and graphics together with text. A multimedia database is a that include one or more primary media file types such as. Multimedia database management system10. 10 multimedia database systems contents i4 lehrstuhl fuer multimedia database content and structure citeseerx. Multimedia database wikipedia multimedia wikipedia en. Multimedia databases are that contain and allow key data management operations with multimedia. The spatial, temporal, storage, retrieval, integration, and presentation requirements of multimedia data differ significantly abruce berra, 'multimedia database systems,' in lecture notes computer science, (advanced systems, edsbhargava n a management system (m dbms) should provide for the ef cient storage manipulation represented as text, images, voice, 28 feb 2011 purpose this study is to review current applications teaching learning, further discuss some issues a(mmdbms) must support types addition providing facilities traditional dbms functions controlled collection items such graphic objects, video audioMultimedia wikipediamultimedia slidesharemultimedia databasemultimedia tech faqintroduction youtubeigi global. Wikipedia wiki multimedia_database url? Q webcache. Multimedia database management systems acm digital library. The multimedia data include one or more primary media types such as text, images, graphic objects (including drawings, sketches and illustrations) animation sequences, audio video 20 dec 2015 database(mmdb)? Multimedia database is a collection of related. Multimedia database wikipediamultimedia slidesharemultimedia databasemultimedia the tech faqintroduction to multimedia youtubeigi global. Multimedia database management requirements citeseerxdistributed multimedia systems. The acquisition, generation a multimedia database management system (mm dbms) is framework that separate the and from application programs definition. Multimedia databases ieee xplore document. Multimedia database applications issues and concerns for multimedia systems where are we now? Itec.
Views: 267 Aile Aile
Big Data Analytics Lectures : Random Sampling Algorithm With solved example in Hindi
 
18:05
visit our website for full course www.lastmomenttuitions.com Random sampling algorithm is used to identify the set of two itemsets which are sampled together most frequently by using buckets and the map-reduce logic . It makes use of random fuction to genrate output. NOTES: https://lastmomenttuitions.com/how-to-buy-notes/ bda notes form : https://goo.gl/Ti9CQj introduction to Hadoop : https://goo.gl/LCHC7Q Introduction to Hadoop part 2 : https://goo.gl/jSSxu2 Distance Measures : https://goo.gl/1NL3qF Euclidean Distance : https://goo.gl/6C16RJ Jaccard distance : https://goo.gl/C6vmWR Cosine Distance : https://goo.gl/Sm48Ny Edit Distance : https://goo.gl/dG3jAP Hamming Distance : https://goo.gl/KNw95L FM Flajolit martin Algorithm : https://goo.gl/ybjX9V Random Sampling Algorithm : https://goo.gl/YW1AWh PCY ( park chen yu) algorithm : https://goo.gl/HVWs21 Collaborative Filtering : https://goo.gl/GBQ7JW Bloom Filter Basic concept : https://goo.gl/uHjX5B Naive Bayes Classifier : https://goo.gl/dbRYYh Naive Bayes Classifier part2 : https://goo.gl/LWstNv Decision Tree : https://goo.gl/5m8JhA Apriori Algorithm :https://goo.gl/mmpxL6 FP TREE Algorithm : https://goo.gl/S29yV8 Agglomerative clustering algorithmn : https://goo.gl/L9nGu8 Hubs and Authority and Hits Algorithm : https://goo.gl/D2EdFG Betweenness Centrality : https://goo.gl/czZZJR
Views: 1658 Last moment tuitions
Architecture of datawarehouse IN HINDI
 
07:18
Sample Notes : https://drive.google.com/file/d/19xmuQO1cprKqqbIVKcd7_-hILxF9yfx6/view?usp=sharing for notes fill the form : https://goo.gl/forms/C7EcSPmfOGleVOOA3 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: 96748 Last moment tuitions
Aidan Horner - How the hippocampus encodes and retrieves complex episodic events
 
58:32
Overview My research interests are broadly related to how the brain remembers information over long periods of time. How are we able to remember life events from weeks, months or even years ago? How are we able to navigate through a city we haven’t visited for several months? I use experimental psychology, virtual reality, brain imaging and computational modelling to understand the neural mechanisms that support long-term memory.
Views: 939 PsyNeuroEvents
Cure Algorithm in Hindi | Big data analytics Tutorials
 
11:05
visit our website for full course www.lastmomenttuitions.com NOTES: https://lastmomenttuitions.com/how-to-buy-notes/ Any doubt ask us and connect us at : you can connect us at Gmail:[email protected] you can email us :[email protected] Whatsapp contact:9762903078 facebook: https://www.facebook.com/lastmomenttu... more videos coming soon subscribe karke rakho tab tak
Views: 3546 Last moment tuitions
Addressing GDPR data discovery requirements with SAP Information Steward
 
13:11
The first step in any data management initiative is to understand the current state of your data. SAP Information Steward software combines data profiling, metadata, stewardship, and governance capabilities into a single solution that enables you to understand: • What systems are collecting personal data • What formats are being used for personal data • How personal data is being categorized and tagged • If personal data is accurate and consistent across sources NOTE: Information in this presentation or communication from SAP in no way guarantees that SAP customers will achieve GDPR compliance. It is the customer’s responsibility to adopt measures that the customer deems appropriate to achieve GDPR compliance.
Views: 917 SAP Technology
Range, variance and standard deviation as measures of dispersion | Khan Academy
 
12:34
Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/probability/descriptive-statistics/variance_std_deviation/e/variance?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Watch the next lesson: https://www.khanacademy.org/math/probability/descriptive-statistics/variance_std_deviation/v/variance-of-a-population?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/descriptive-statistics/box-and-whisker-plots/v/range-and-mid-range?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it! About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to KhanAcademy’s Probability and Statistics channel: https://www.youtube.com/channel/UCRXuOXLW3LcQLWvxbZiIZ0w?sub_confirmation=1 Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 1110172 Khan Academy
UMBC's GIS Master's Program Webinar - Big Social Data Analysis
 
56:19
Why GIS at UMBC? http://www.umbc.edu/gis/ Big Social Data Analysis: Using location & twitter to explore the tragic aftermath of the Sandy Hook Elementary School shooting. Categorization is a common pursuit in data analysis. Its goal is to discover largely homogonized structures in data using supervised or unsupervised ways of learning. The discovery of these structures can be learned when the data generating process is stationary over space. This case study will outline (1) how effective natural language processing can be in exposing these structures, (2) how critical a geographic perspective is when analyzing data over space, and (3) the utility of Twitter in social science research. Presented by Rich Heimann
Geographic Information System(GIS) Part-2 For SSC Scientific Assistant(Cs/IT) 2017
 
14:11
In this video,I have explained the geographic information system GIS spatial model in detail For SSC Scientific Assistant Exam and NIC Exam 2017 .For notes download Complete Theory IT Notes Ebook. Link below to download sample of ebook and complete ebook. -----------------------------------------------------------------------------------------------------------Sample of Ebook: https://drive.google.com/file/d/0Bx5dlc6w4ab2V1RsVWNFZVVwWkk/view ---------------------------------------------------------------------------------------------------------- Download Full Ebook For Paper 2(CS/IT) http://studyregular.in/professional-knowledge-complete-theory-it-ebook-for-ibps-rrb-scale-2sbi-itibps-itinsurance-specialist-exam-2017-18/ ----------------------------------------------------------------------------------------------------------- 1000+ MCQ Ebook: https://www.instamojo.com/studyregular/it-officer-ebook1000-questions/ ---------------------------------------------------------------------------------------------------------- Telegram Channel Study Regular IBPS/SBI IT OFFICER,SSC,NIELIT Link: https://t.me/studyregular Telegram SSC Scientific Assistant Physics: https://t.me/sscphysics Telegram Intelligence Bureau Exam: https://t.me/studyregularIB ----------------------------------------------------------------------------------------------------------- SSC Scientific Assistant Paper 1 Crack Strategy and Books: https://youtu.be/_yN-6l9tRWw ----------------------------------------------------------------------------------------------------------- Our Facebook Group: https://www.facebook.com/groups/372637659746460/?ref=bookmarks ----------------------------------------------------------------------------------------------------------- Our Facebook Page: https://www.facebook.com/studyregular30/ ----------------------------------------------------------------------------------------------------------- Our Website For MCQ and Other Notes: www.studyregular.in -----------------------------------------------------------------------------------------------------------
Views: 6629 Study Regular
Meet a Surveyor with Student Edge
 
04:06
Interested in becoming a Surveyor? We caught up with Matt to learn all about what goes into mapping the land and environment. A surveyor collects and measures spatial information about the land and environment, including natural and constructed features such as open pit mines, coastlines, marine floors and underground works. This information can then be used by geographic information science specialists and cartographers to analyse and model the data, construct maps, plans, files, charts and reports.
Views: 640 Student Edge
Lecture - 30 Introduction to Data Warehousing and OLAP
 
57:50
Lecture Series on Database Management System by Dr.S.Srinath, IIIT Bangalore. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 208924 nptelhrd
O'Reilly Webcast: Python for Data Analysis
 
57:14
*Note: Audio quality a little poor. Finding great data analysts is difficult. Despite the explosive growth of data in industries ranging from manufacturing and retail to high technology, finance, and healthcare, learning and accessing data analysis tools has remained a challenge. This webcast will highlight one of the most important tools in the field—Python. In this hands-on webcast presented by Wes McKinney, author of "Python for Data Analysis", he will showcase a number of examples and you will receive an introduction to some of the most important tools in the Python language for: data preparation data analysis data visualization Learn about the growing field of data analysis from an expert in the community. About Wes McKinney Wes McKinney is CTO and Cofounder of Lambda Foundry, Inc. From 2010 to 2012, he served as a Python consultant to hedge funds and banks while developing pandas, a widely used Python data analysis library. From 2007 to 2010, he researched global macro and credit trading strategies at AQR Capital Management. He graduated from MIT with an S.B. in Mathematics. He is on leave from the Duke University Ph.D program in Statistics. Produced by: Yasmina Grecp
Views: 5382 O'Reilly