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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: 135047 Well Academy
12. Clustering
 
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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: John Guttag Prof. Guttag discusses clustering. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 62218 MIT OpenCourseWare
Lecture 58 — Overview of Clustering | Mining of Massive Datasets | Stanford University
 
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. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "FAIR USE" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .
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: 355245 MIT OpenCourseWare
Data Structures and Algorithms Complete Tutorial Computer Education for All
 
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Computer Education for all provides complete lectures series on Data Structure and Applications which covers Introduction to Data Structure and its Types including all Steps involves in Data Structures:- Data Structure and algorithm Linear Data Structures and Non-Linear Data Structure on Stack Data Structure on Arrays Data Structure on Queue Data Structure on Linked List Data Structure on Tree Data Structure on Graphs Abstract Data Types Introduction to Algorithms Classifications of Algorithms Algorithm Analysis Algorithm Growth Function Array Operations Two dimensional Arrays Three Dimensional Arrays Multidimensional arrays Matrix operations Operations on linked lists Applications of linked lists Doubly linked lists Introductions to stacks Operations on stack Array based implementation of stack Queue Data Structures Operations on Queues Linked list based implementation of queues Application of Trees Binary Trees Types of Binary Trees Implementation of Binary Trees Binary Tree Traversal Preorder Post order In order Binary Search Tree Introduction to Sorting Analysis of Sorting Algorithms Bubble Sort Selection Sort Insertion Sort Shell Sort Heap Sort Merge Sort Quick Sort Applications of Graphs Matrix representation of Graphs Implementations of Graphs Breadth First Search Topological Sorting Subscribe for More https://www.youtube.com/channel/UCiV37YIYars6msmIQXopIeQ Find us on Facebook: https://web.facebook.com/Computer-Education-for-All-1484033978567298 Java Programming Complete Tutorial for Beginners to Advance | Complete Java Training for all https://youtu.be/gg2PG3TwLx4
Algorithms for Big Data (COMPSCI 229r), Lecture 1
 
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Logistics, course topics, basic tail bounds (Markov, Chebyshev, Chernoff, Bernstein), Morris' algorithm.
Views: 82838 Harvard University
Lecture 12: TextMining
 
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Techniques to extract information from textual data. Course homepage: http://www.knoesis.org/cs4800-6800-spring2016
Views: 1081 Knoesis Center
Data mining tutorial for beginners FREE Training 01
 
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Published on Aug 2, 2014 1 intro data mining and scraping next tutorial here: http://youtu.be/gb4ufqFkT7A please comment below if you have any questions. Tq Category Education License Standard YouTube License
Views: 104091 Red Team Cyber Security
Best Practices in Data Mining & Link Analysis
 
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In January, 2016, Crime Tech Solutions - Your Source for Investigation Software - proudly offered a free informational webinar to members of International Association of Crime Analysts (IACA). With renowned expert and published author Chris Westphal as speaker, the webinar seats immediately filled. This is an abbreviated version for those either unable to attend, or simply interested in best practices in data mining and link visualization.
Views: 1632 Doug Wood
Deep Learning: Intelligence from Big Data
 
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Deep Learning: Intelligence from Big Data Tue Sep 16, 2014 6:00 pm - 8:30 pm Stanford Graduate School of Business Knight Management Center – Cemex Auditorium 641 Knight Way, Stanford, CA A machine learning approach inspired by the human brain, Deep Learning is taking many industries by storm. Empowered by the latest generation of commodity computing, Deep Learning begins to derive significant value from Big Data. It has already radically improved the computer’s ability to recognize speech and identify objects in images, two fundamental hallmarks of human intelligence. Industry giants such as Google, Facebook, and Baidu have acquired most of the dominant players in this space to improve their product offerings. At the same time, startup entrepreneurs are creating a new paradigm, Intelligence as a Service, by providing APIs that democratize access to Deep Learning algorithms. Join us on September 16, 2014 to learn more about this exciting new technology and be introduced to some of the new application domains, the business models, and the key players in this emerging field. Moderator Steve Jurvetson, Partner, DFJ Ventures Panelists Adam Berenzweig, Co-founder and CTO, Clarifai Naveen Rao, Co-founder and CEO, Nervana Systems Elliot Turner, Founder and CEO, AlchemyAPI Ilya Sutskever, Research Scientist, Google Brain Demo Companies**: Clarifai | SkyMind | Ersatz Labs | AlchemyAPI ** Follow (@VLAB) on Twitter and Event Hashtag #VLABdl
Views: 541251 vlabvideos
Educational Data Mining: Predict the Future, Change the Future
 
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Teachers College is proud to introduce the 2012-13 Julius and Rosa Sachs Distinguished Lecturer Professor Ryan Baker, Columbia University. Ryan Shaun Joazeiro de Baker is Visiting Associate Professor in the Department of Human Development. He earned his Ph.D. in Human-Computer Interaction from Carnegie Mellon University, and was a post-doctoral fellow in the Learning Sciences at the University of Nottingham. He earned his Bachelor's Degree (Sc.B.) in Computer Science from Brown University. Dr. Baker has been Assistant Professor of Psychology and the Learning Sciences at Worcester Polytechnic Institute. He previously served as the first Technical Director of the Pittsburgh Science of Learning Center DataShop, the largest public repository for data on the interaction between learners and educational software. He is currently serving as the founding President of the International Educational Data Mining Society, and as Associate Editor of the Journal of Educational Data Mining. His research combines educational data mining, learning analytics and quantitative field observation methods in order to better understand how students respond to educational software, and how these responses impact their learning. He studies these issues within intelligent tutors, simulations, and educational games. In recent years, he and his colleagues have developed strategies to make inferences in real-time about students' motivation, meta-cognition, affect, and robust learning.
Data Mining Lecture 1 Part 1
 
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Introduction
Views: 4101 Utah Data
Business Data Mining Lecture 3 Business Intelligence & Business Analytics Part 1
 
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Business Data Mining Lecture 3 Business Intelligence & Business Analytics Part 1
Views: 70 Phayung Meesad
Data Mining: Mastering Data Mining Skills | Part - 1
 
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In this video, Qasim Ali Shah talking on the topic "DATA MINING SKILLS". In this session you will know about the content of trainers. He is giving some useful tips to all students, like: how should you can select your topic to speak effectively and after this what type of content will be helpful for your topic. You will know so many more after watching this video regarding above given topic. ===== ABOUT Qasim Ali Shah ===== Qasim Ali Shah is a Public Speaker- Teacher- Writer- Corporate Trainer & Leader for every age group- Businessmen- Corporate executives- Employees- Students- Housewives- Networkers- Sportsmen and for all who wish everlasting Success- Happiness- Peace and Personal Growth. He helps people to change their belief & thought pattern- experience less stress and more success in their lives through better communication- positive thinking and spiritual knowledge. ===== FOLLOW ME ON THE SOCIALS ===== - Qasim Ali Shah: https://goo.gl/6BKcxu - Google+: https://goo.gl/uPyGvT - Twitter: https://goo.gl/78MVoA - Website : https://goo.gl/Tgjy6u ===== Team Member: Waqas Nasir =====
Views: 8949 Qasim Ali Shah
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: 209785 nptelhrd
Decision Tree with Solved Example in English | 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 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: 132928 Last moment tuitions
Lecture 1 | Machine Learning (Stanford)
 
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Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng provides an overview of the course in this introductory meeting. This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=A89DCFA6ADACE599 CS 229 Course Website: http://www.stanford.edu/class/cs229/ Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford
Views: 2039789 Stanford
Lecture 60 — The k Means Algorithm | Stanford University
 
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. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "FAIR USE" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .
Data Mining  (Session 1)
 
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BEST DATA MINING LECTURE
Views: 37 aviral pal
Lecture 01
 
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introduction to Business analytics and data mining modeling using R studio Discussions on key terms used for data mining finally discuss the course roadmap
INTRODUCTION TO DATA MINING
 
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INTRODUCTION TO DATA MINING
Views: 13549 LearnEveryone
Data Mining Lecture 26 Part 2
 
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Graph Analysis : Graph Sparsification
Views: 108 Utah Data
Data Mining - Leveraging Noisy Lists for Social Feed Ranking | Lectures On-Demand
 
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Matthew Burgess, Computer Science and Engineering - University of Michigan The 4th University of Michigan Data Mining Workshop Sponsored by Computer Science and Engineering, Yahoo!, and Office of Research Cyberinfrastructure (ORCI) Faculty, staff, and graduate students working in the fields of data mining, broadly construed. This workshop will present techniques: models and technologies for statistical data analysis, Web search technology, analysis of user behavior, data visualization, etc. We speak about data-centric applications to problems in all fields, whether it is in the natural sciences, the social sciences, or something else.
Data Mining - Foundations of Learning to Rank: Needs & Challenges | Lectures On-Demand
 
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Ambuj Tewari - EECS at the University of Michigan The 4th University of Michigan Data Mining Workshop Sponsored by Computer Science and Engineering, Yahoo!, and Office of Research Cyberinfrastructure (ORCI) Faculty, staff, and graduate students working in the fields of data mining, broadly construed. This workshop will present techniques: models and technologies for statistical data analysis, Web search technology, analysis of user behavior, data visualization, etc. We speak about data-centric applications to problems in all fields, whether it is in the natural sciences, the social sciences, or something else.
Views: 3175 Michigan Engineering
Data Mining Lecture - - Data Analytics life cycle (Eng-Hindi)
 
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Business Intelligence Big data issues are solved using data analytics life cycle The key roles of data analytics are explained -~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 16871 Well Academy
Decision Tree 1: how it works
 
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Full lecture: http://bit.ly/D-Tree A Decision Tree recursively splits training data into subsets based on the value of a single attribute. Each split corresponds to a node in the. Splitting stops when every subset is pure (all elements belong to a single class) -- this can always be achieved, unless there are duplicate training examples with different classes.
Views: 440760 Victor Lavrenko
Lecture 46 — Dimensionality Reduction - Introduction | Stanford University
 
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. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "FAIR USE" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .
Data Collection and Preprocessing | Lecture 6
 
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Deep Learning Crash Course playlist: https://www.youtube.com/playlist?list=PLWKotBjTDoLj3rXBL-nEIPRN9V3a9Cx07 Highlights: Garbage-in, Garbage-out Dataset Bias Data Collection Web Mining Subjective Studies Data Imputation Feature Scaling Data Imbalance #deeplearning #machinelearning
Views: 746 Leo Isikdogan
Machine Learning #73 BIRCH Algorithm | Clustering
 
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Machine Learning #73 BIRCH Algorithm | Clustering In this lecture of machine learning we are going to see BIRCH algorithm for clustering with example. BIRCH algorithm (balanced iterative reducing and clustering using hierarchies) is an unsupervised data mining algorithm which is used to perform hierarchical clustering over particularly large data-sets.The advantage of using BIRCH algorithm is its ability to incrementally & dynamically cluster incoming, multi-dimensional metric data points in an attempt to produce the best quality clustering for a given set of resources (memory and time constraints). single scan of the database is needed by BIRCH algorithm in most of the cases. Machine Learning Complete Tutorial/Lectures/Course from IIT (nptel) @ https://goo.gl/AurRXm Discrete Mathematics for Computer Science @ https://goo.gl/YJnA4B (IIT Lectures for GATE) Best Programming Courses @ https://goo.gl/MVVDXR Operating Systems Lecture/Tutorials from IIT @ https://goo.gl/GMr3if MATLAB Tutorials @ https://goo.gl/EiPgCF
Views: 5561 Xoviabcs
Introduction to Data Mining: Data Quality
 
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In this next topic, we introduce the most overlooked step in data mining, Data Quality. -- At Data Science Dojo, we're extremely passionate about data science. Our in-person data science training has been attended by more than 3500+ employees from over 700 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8M2X0 See what our past attendees are saying here: https://hubs.ly/H0f8M330 -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... -- Vimeo: https://vimeo.com/datasciencedojo
Views: 4756 Data Science Dojo
Machine Learning #75 Density Based Clustering
 
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Machine Learning #75 Density Based Clustering Machine Learning Complete Tutorial/Lectures/Course from IIT (nptel) @ https://goo.gl/AurRXm Discrete Mathematics for Computer Science @ https://goo.gl/YJnA4B (IIT Lectures for GATE) Best Programming Courses @ https://goo.gl/MVVDXR Operating Systems Lecture/Tutorials from IIT @ https://goo.gl/GMr3if MATLAB Tutorials @ https://goo.gl/EiPgCF
Views: 2194 Xoviabcs
Machine Learning Algorithms | Machine Learning Tutorial | Data Science Training | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This Machine Learning Algorithms Tutorial shall teach you what machine learning is, and the various ways in which you can use machine learning to solve a problem! Towards the end, you will learn how to prepare a dataset for model creation and validation and how you can create a model using any machine learning algorithm! In this Machine Learning Algorithms Tutorial video you will understand: 1) What is an Algorithm? 2) What is Machine Learning? 3) How is a problem solved using Machine Learning? 4) Types of Machine Learning 5) Machine Learning Algorithms 6) Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #MachineLearningAlgorithms #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "
Views: 134926 edureka!
GA Intro to Data Science - Lecture 3: Data Mining
 
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General Assembly's 20th NYC Data Science Course
Views: 959 Aerlinger
Lecture 08 - Bias-Variance Tradeoff
 
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Bias-Variance Tradeoff - Breaking down the learning performance into competing quantities. The learning curves. Lecture 8 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website - http://work.caltech.edu/telecourse.html Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommons.org/licenses/by-nc-nd/3.0/ This lecture was recorded on April 26, 2012, in Hameetman Auditorium at Caltech, Pasadena, CA, USA.
Views: 95712 caltech
4 Concept Description Characterization and Comparison- Data Warehouse and Data Mining
 
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http://www.atozsky.com/ https://www.facebook.com/atozsky.computer/ All credits goes to NIELIT, Delhi INDIA
Views: 654 AtoZ COMPUTER
Data Mining Lecture 19 Part 3
 
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Noise : Noise in Data
Views: 46 Utah Data
Introduction to Data Mining: Feature Subset Selection
 
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In part six of data preprocessing, we discuss another way of dimensionality reduction, feature subset selection. -- At Data Science Dojo, we're extremely passionate about data science. Our in-person data science training has been attended by more than 3500+ employees from over 700 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8Lrw0 See what our past attendees are saying here: https://hubs.ly/H0f8M7M0 -- Like Us: https://www.facebook.com/datascienced... Follow Us: https://plus.google.com/+Datasciencedojo Connect with Us: https://www.linkedin.com/company/data... Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_scienc... -- Vimeo: https://vimeo.com/datasciencedojo
Views: 4386 Data Science Dojo
INTRODUCTION TO DATA MINING IN HINDI
 
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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: 99918 LearnEveryone
Data Mining | What is Data Mining - Imarticus
 
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Know more about Data Mining and its applications. The Post Graduate Program in Data Analytics is a 500+ hour program covering foundational concepts and hands-on learning of leading analytical tools, such as SAS, R, Python, Hive, Spark and Tableau as well as functional analytics across many domains. Over the course of 3 semesters, candidates will not only gain theoretical knowledge of data science tools, but also gain exposure to business perspectives and industry best practices through guest lectures and project submissions. Click here to know more about the Program http://imarticus.org/post-graduate-program-in-data-analytics Imarticus Learning is a professional education institute focused on bridging the gap between industry & academia by offering certified industry-endorsed courses in Financial Services, Business Analysis, Business Analytics & Wealth Management. Visit: http://www.imarticus.org
Views: 197 Imarticus Learning
Lecture 11 - Overfitting
 
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Overfitting - Fitting the data too well; fitting the noise. Deterministic noise versus stochastic noise. Lecture 11 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunes.apple.com/us/course/machine-learning/id515364596 and on the course website - http://work.caltech.edu/telecourse.html Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about this license, http://creativecommons.org/licenses/by-nc-nd/3.0/ This lecture was recorded on May 8, 2012, in Hameetman Auditorium at Caltech, Pasadena, CA, USA.
Views: 74656 caltech
Statistical Aspects of Data Mining (Stats 202) Day 9
 
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Google Tech Talks July 24, 2007 ABSTRACT This is the Google campus version of Stats 202 which is being taught at Stanford this summer. I will follow the material from the Stanford class very closely. That material can be found at www.stats202.com. The main topics are exploring and visualizing data, association analysis, classification, and clustering. The textbook is Introduction to Data Mining by Tan, Steinbach and Kumar. Googlers are welcome to attend any classes which they think might be of interest to them. Credits: Speaker:David Mease
Views: 12631 GoogleTechTalks
Prescription  Data Mining  and  You
 
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Created on March 27, 2009 using FlipShare.
Views: 1233 HCFAMA
6 Types of Classification Algorithms
 
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Here are some of the most commonly used classification algorithms -- Logistic Regression, Naïve Bayes, Stochastic Gradient Descent, K-Nearest Neighbours, Decision Tree, Random Forest and Support Vector Machine. https://analyticsindiamag.com/7-types-classification-algorithms/ -------------------------------------------------- Get in touch with us: Website: www.analyticsindiamag.com Contact: [email protected] Facebook: https://www.facebook.com/AnalyticsIndiaMagazine/ Twitter: http://www.twitter.com/analyticsindiam Linkedin: https://www.linkedin.com/company-beta/10283931/ Instagram: https://www.instagram.com/analyticsindiamagazine/
Agglomerative clustering  algorithmn with example |data mining lectures|machine learning
 
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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: 71064 Last moment tuitions
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.
Data Warehousing and Data Mining
 
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A short video to describe data warehousing and data mining
Views: 4666 Mcdev777
Lecture 49 — SVD Gives the Best Low Rank Approximation (Advanced) | Stanford
 
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. Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for "FAIR USE" for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use. .
Weka Data Mining Tutorial for First Time & Beginner Users
 
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23-minute beginner-friendly introduction to data mining with WEKA. Examples of algorithms to get you started with WEKA: logistic regression, decision tree, neural network and support vector machine. Update 7/20/2018: I put data files in .ARFF here http://pastebin.com/Ea55rc3j and in .CSV here http://pastebin.com/4sG90tTu Sorry uploading the data file took so long...it was on an old laptop.
Views: 422063 Brandon Weinberg