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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: 143937 Last moment tuitions
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: 8833 Last moment tuitions
INTRODUCTION TO DATA MINING IN HINDI
 
15:39
Buy Software engineering books(affiliate): Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2whY4Ke Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2wfEONg Software Engineering: A Practitioner's Approach (India) by McGraw-Hill Higher Education https://amzn.to/2PHiLqY Software Engineering by Pearson Education https://amzn.to/2wi2v7T Software Engineering: Principles and Practices by Oxford https://amzn.to/2PHiUL2 ------------------------------- find relevant notes at-https://viden.io/
Views: 99889 LearnEveryone
Spatial interpolation techniques
 
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Spatial Interpolation techniques
Spatial Analysis for Urban Planning Demo
 
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See how new regression analysis tools in ArcGIS 9.3 allow planners to discover relationships key to predicting urban growth. Recorded at the 2008 ESRI International User Conference.
Views: 33327 esri
Data Mining, Classification, Clustering, Association Rules, Regression, Deviation
 
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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: 81319 StudyYaar.com
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: 70958 Last moment tuitions
Spatial Query and Analysis in GIS in HINDI
 
10:46
Buy GIS books (affiliate): Remote Sensing and GIS https://amzn.to/2Ce41NL Advanced Surveying: Total Station, GPS, GIS & Remote Sensing by Pearson https://amzn.to/2wEAXcj An Introduction to Geographic Information Technology https://amzn.to/2Q2XuID Mastering QGIS https://amzn.to/2oFi717 QGIS Python Programming Cookbook https://amzn.to/2wHUkSu QGIS: Becoming a GIS Power User https://amzn.to/2PYCz9D Remote Sensing: Principles and Applications https://amzn.to/2Q4Wi7x Gis: Fundamentals, Applications and Implementations https://amzn.to/2Q5iFK6 Remote Sensing and Geographical Information Systems: Basics and Applications https://amzn.to/2Q2dI4y Textbook of Remote Sensing and Geographical Information Systems https://amzn.to/2Q748h9 Remote Sensing and GIS in Environment Resource Management https://amzn.to/2Q2fpPs ------------------------------------- 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: 1731 LearnEveryone
Concept Hierarchies - Georgia Tech - KBAI: Part 2
 
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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: 4187 Udacity
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: 7375 Microsoft Research
Data Mining  Association Rule - Basic Concepts
 
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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.
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: 50592 Last moment tuitions
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: 209743 Last moment tuitions
SDMS - Spatial Data Management System - MIT 1980
 
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An updated version of the 1978 Master's Thesis by William Donelson, B.S. 1975, M.S. 1978 MIT. This version created 1978-1980 with the assitance of Chris Schmandt, Joe Rice, Ben McCann,Steve Tufty and Rimas Ignaitis. Richard Bolt shown in chair. Notes: 1. video mostly silent, but sections with audio do exist 2. audio track repaired by W. Donelson 2012 © MIT Media Lab 1980 under the direction of Prof Nicholas Negroponte http://dl.acm.org/citation.cfm?id=807391
Views: 10887 William Donelson
11. Introduction to Machine Learning
 
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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: 354493 MIT OpenCourseWare
mod01lec02
 
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Views: 8265 Data Mining - IITKGP
Gestalt Principles and Visualization Process -- Introduction to Data Visualization 1.3
 
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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: 155 Jonathan Dinu
Geostatistics Basics
 
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Lecture by Luc Anselin on point pattern analysis (2006)
Views: 9375 GeoDa Software
Getting Started with Spatial Data Analysis in R
 
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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: 41254 Domino Data Lab
Apriori Algorithm with solved example|Find frequent item set in hindi | DWM | ML | BDA
 
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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: 126680 Last moment tuitions
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: 30529 Last moment tuitions
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: 8580 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: 106413 Last moment tuitions
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: 67940 Last moment tuitions
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: 1610 Lisa Berry
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: 31190 Last moment tuitions
what is  Olap operation in hindi
 
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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: 129725 Last moment tuitions
Inferring Road Maps from GPS Traces
 
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Google Tech Talk March 7, 2013 (more info below) Presented by James Biagioni ABSTRACT Driven by the near-ubiquitous availability of GPS sensors in a variety of everyday devices, the past decade has witnessed considerable interest in the automatic inference and construction of road maps from GPS traces. Existing methods for performing this task can be largely divided into three categories: k-means clustering, trace merging, and kernel density estimation. In this talk I discuss the three classes of existing algorithms guided by examples from canonical work in the literature, and illustrate their strengths and weaknesses. In light of these findings I then introduce and explain the operation of our new hybrid map inference algorithm, developed to overcome these existing methods' limitations with GPS-trace coverage disparity and measurement error. Lastly, I discuss some directions for future work in this problem domain. For further details on the material presented in this talk, please refer to the following research papers: James Biagioni and Jakob Eriksson. "Map Inference in the Face of Noise and Disparity." In SIGSPATIAL GIS, pages 79-88. ACM, 2012. Xuemei Liu, James Biagioni, Jakob Eriksson, Yin Wang, George Forman, and Yanmin Zhu. "Mining Large-Scale, Sparse GPS Traces for Map Inference: Comparison of Approaches." In KDD, pages 669-677. ACM, 2012. James Biagioni and Jakob Eriksson. "Inferring Road Maps from GPS Traces: Survey and Comparative Evaluation." In 91st Annual Meeting of the Transportation Research Board, 2012. All of which are freely-available on my website: http://www.cs.uic.edu/Bits/JamesBiagioni Speaker Bio James Biagioni is a PhD candidate in his final year at the University of Illinois at Chicago, where he is advised by Professor Jakob Eriksson in the BITS Networked Systems Laboratory. James' research interests are centered around the problem of inferring interesting and useful phenomena from sensor data, and its applications.
Views: 6203 GoogleTechTalks
Architecture of datawarehouse IN HINDI
 
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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: 105704 Last moment tuitions
Data Mining Lecture -- Decision Tree | Solved Example (Eng-Hindi)
 
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-~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 134924 Well Academy
Decision tree with solved example in hindi (ID3 algorithm) | Artificial intelligence series
 
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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: 110528 Last moment tuitions
Aidan Horner - How the hippocampus encodes and retrieves complex episodic events
 
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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: 973 PsyNeuroEvents
Spatial Data Science con R (English subtitles)
 
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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: 2603 Alí Santacruz
Mining Geostatistics
 
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Views: 34 KIMO AFUKE
Sampling: Simple Random, Convenience, systematic, cluster, stratified - Statistics Help
 
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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: 657863 Dr Nic's Maths and Stats
Range, variance and standard deviation as measures of dispersion | Khan Academy
 
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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: 1165129 Khan Academy
Simple Linear Regression (Supervised Machine Learning) [R Data Science Tutorial 11 (a)]
 
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This tutorial is about starting with supervised machine learning such as how to make a simple linear regression model. How to train the model and use it for predicting output with a new data set. Note: Simple Linear regression is used, when the output or outcome variable is continuous. For example speed, price, temperature etc.
Views: 38 Rahul_CODIFY
Lecture - 34 Data Mining and Knowledge Discovery
 
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Lecture Series on Database Management System by Dr. S. Srinath,IIIT Bangalore. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 132897 nptelhrd
The problem of institutional fit in complex systems
 
49:00
In this lecture on the challenges and opportunities for governance in complex systems, Dr. Oran Young first focuses on the role of institutions and governance systems as mechanisms for steering individual and social behavior to reach shared goals. He notes that one role for governance systems is to address specific problems identified by society, and he emphasizes that collective action problems are one type of problem that requires institutions to redirect individual actions that, when aggregated, can cause or exacerbate, social and environmental problems. He highlights the challenges posed by complex systems and uncertainty within them, using examples from global climate agreements and other environmental governance systems that use different approaches to induce change or steer individual behavior. Spatial and membership mismatches often challenge the ability of these governance systems to reach the desired goal, and he notes that as the need for coordinated global action on managing human impacts on the environment increases, we will need to explore new dimensions and connections among governance systems. He concludes by noting that complex problems require institutions that are agile and adaptive to changing information and understandings of the system. More information on the Immersion Program and other lectures can be found here: http://www.sesync.org/for-you/educator/programs/immersion.
Views: 228 sesync annapolis
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: 171762 Nando de Freitas
Cycling - Space-time analysis
 
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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: 153 Robin Lovelace
GPS to GIS: Post-Field Data Collection Considerations
 
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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
How to run cluster analysis in Excel
 
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A step by step guide of how to run k-means clustering in Excel. Please note that more information on cluster analysis and a free Excel template is available at http://www.clusteranalysis4marketing.com
Views: 78181 MktgStudyGuide
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: 24596 Harvard GSD
Open Science: RKWard Overview
 
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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: 3499 hyperscientist
Lecture - 30 Introduction to Data Warehousing and OLAP
 
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Lecture Series on Database Management System by Dr.S.Srinath, IIIT Bangalore. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 209776 nptelhrd
UMBC's GIS Master's Program Webinar - Big Social Data Analysis
 
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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
ECONOMETRICS time series regression problems economics isi dse+study material+online lectures
 
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ECONOMETRICS time series regression problems economics isi dse+study material+online lectures VISIT OUR WEBSITE https://www.souravsirclasses.com/ FOR COMPLETE LECTURES / STUDY MATERIALS /NOTES /GUIDENCE / PAST YEAR SOLVED +SAMPLE PAPAERS /TRICKS /MCQ / SHORT CUT/ VIDEO LECTURES /LIVE + ONLINE CLASSES GIVE US A CALL / WHAST APP AT 9836793076 Also find us at…. BLOGSPOT http://souravdas3366.blogspot.com/ SLIDES ON COURSES https://www.slideshare.net/Souravdas31 TWITTER https://twitter.com/souravdas3366 FACEBOOK https://www.facebook.com/Sourav-Sirs-... LINKED IN https://www.linkedin.com/in/sourav-da... GOOGLE PLUS https://plus.google.com/+souravdassou... econometrics academy, econometrics academy stata, econometrics analysis, econometrics and operations research, econometrics assumptions, econometrics calculation, econometrics career, econometrics class, econometrics course, econometrics efficiency, econometrics endogeneity, econometrics error correction model, econometrics for beginners, econometrics for finance, econometrics formulas, econometrics full course, econometrics graduate level, econometrics gujarati, econometrics gujarati solutions, econometrics in finance, econometrics interaction term, econometrics khan academy, econometrics lecture harvard, econometrics mark thoma time series analysis, regression coefficient, regression data analysis, regression data mining, regression discontinuity design, regression equation, regression graph, regression in statistics time series basic concepts, time series bcom, time series big data, time series cointegration, time series components, time series data, time series data science, time series forecasting, time series in statistics, time series khan academy