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Data Mining & Business Intelligence | Tutorial #15 | Data Reduction - Data Cube Aggregation
 
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Order my books at 👉 http://www.tek97.com/ #DataReduction #DataCubeAggregation Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj See the detailed explanation about Data Cube Aggregation in Data Mining as part of Data Reduction step. Watch now ! انظر الشرح التفصيلي حول تجميع بيانات المكعب في Data Mining كجزء من خطوة تقليل البيانات. شاهد الآن ! Weitere Informationen zur Datenwürfelaggregation im Data Mining finden Sie im Abschnitt Datenreduktion. Schau jetzt ! Consultez l'explication détaillée sur l'agrégation de cubes de données dans l'exploration de données dans le cadre de l'étape de réduction des données. Regarde maintenant ! Подробное описание агрегации Data Cube в Data Mining см. В разделе шага Data Reduction. Смотри ! Consulte la explicación detallada sobre la agregación de cubo de datos en la minería de datos como parte del paso de reducción de datos. Ver ahora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 2823 Ranji Raj
Introduction to data mining and architecture  in hindi
 
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Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 177937 Last moment tuitions
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: 103945 LearnEveryone
Data Mining & Business Intelligence | Tutorial #18 | Data Reduction - Numerosity Reduction
 
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Order my books at 👉 http://www.tek97.com/ #DataReduction #NumerosityReduction Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Watch this video to understand what is Numerosity Reduction as part of Data Reduction in Data Mining. Watch now ! شاهد هذا الفيديو لفهم ما هو تخفيض العداد كجزء من الحد من البيانات في استخراج البيانات. شاهد الآن ! Sehen Sie sich dieses Video an, um zu verstehen, was Numerositätsreduktion als Teil der Datenreduktion im Data Mining darstellt. Schau jetzt ! Regardez cette vidéo pour comprendre ce qu'est la réduction de la numération dans le cadre de la réduction des données dans l'exploration de données. Regarde maintenant ! Посмотрите это видео, чтобы понять, что такое Numerosity Reduction как часть сокращения данных в интеллектуальном анализе данных. Смотри ! Mire este video para comprender qué es Numerosity Reduction como parte de la reducción de datos en Data Mining. Ver ahora ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1103 Ranji Raj
Data Mining   KDD Process
 
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KDD - knowledge discovery in Database. short introduction on Data cleaning,Data integration, Data selection,Data mining,pattern evaluation and knowledge representation.
What is Open Data ? EXPLAINED
 
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what is open data what is open database connectivity what is open data science what is open data portal what is open data policy what is open data protocol what is open data kit what is open database what is open data platform what is open dataset in abap what is open data science what is open data portal what is open data policy what is open data protocol what is open data kit what is open data platform what is open data path in as400 what is open data plane what is open data what is open data government open database connectivity open source database what is open data and big data what is open data api what is open data access what is open data center alliance what is open data path in as400 what is open data and big data what is an open data portal what is an open data set what is arcgis open data what is an open data model what is an open data policy what is open data center what is open data canada open database connectivity what is open science data cloud what is linked open data cloud what is an open data company what is open data day what is open diagnostic data exchange what is open data and big data open data institute what is open data what is open ended data what is open diagnostic data exchange what is open data format what to open .data files with is open data free what program to open data files what is talend open studio for data integration what is open data government what is open graph data what is open data in gis what is open hashing in data structures what is open data initiative what is open data institute what is open data in gis what is open data in government what is open data path in as400 what is talend open studio for data integration what is open data kit what is open data model what is open data movement what is open source data mining what is open graph meta data openstreetmap data what does open data mean what is facebook open graph meta data what is open data network what is open data link interface what is open linked data what is linked open data cloud what is open data protocol odata what is os open data what is the definition of open data what is data pilot in open office open data institute what is open data what is open data portal what is open data policy what is open data protocol what is open data platform what is open data path in as400 what is open data plane what is open data philippines what is open data path what is open data ppt what is open data pdf what is open data qld what is open data revolution what is open data science what is open data source what is open data set what is open data stream what is open data source in sql what is open data standard what is open source data mining what is open science data cloud open source database what is open addressing in data structure what is the open data movement what is the open data initiative
Views: 1208 Tech Toons
Introduction to Datawarehouse in hindi | Data warehouse and data mining Lectures
 
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#datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 247993 Last moment tuitions
Data Mining Presentation
 
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Brief overview of data mining
Views: 349 mgiuliano8198
Interview with a Data Scientist
 
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This video is part of the Udacity course "Intro to Programming". Watch the full course at https://www.udacity.com/course/ud000
Views: 285633 Udacity
Data Mining & Business Intelligence | Tutorial #16 | Data Reduction - Attribute Subset Selection
 
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Order my books at 👉 http://www.tek97.com/ #DataReduction #AttributeSubsetSelection Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj Confused about Attribute Subset Selection in Data Mining well this video can help you . Watch now ! ارتباك حول اختيار مجموعة فرعية سمة في استخراج البيانات بشكل جيد هذا الفيديو يمكن أن تساعدك. شاهد الآن ! Confundido acerca de la selección de subconjuntos de atributos en Data Mining, este video puede ayudarlo. Ver ahora ! Смутно о выборе подмножества атрибутов в Data Mining, это видео может вам помочь. Смотри ! Verwirrt über Attribut-Subset-Auswahl in Data Mining gut dieses Video kann Ihnen helfen. Schau jetzt ! Confus à propos de la sélection de sous-ensemble d'attributs dans Data Mining, cette vidéo peut vous aider. Regarde maintenant ! ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ Add me on Facebook 👉https://www.facebook.com/renji.nair.09 Follow me on Twitter👉https://twitter.com/iamRanjiRaj Read my Story👉https://www.linkedin.com/pulse/engineering-my-quadrennial-trek-ranji-raj-nair Visit my Profile👉https://www.linkedin.com/in/reng99/ Like TheStudyBeast on Facebook👉https://www.facebook.com/thestudybeast/ ⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐ For more such videos LIKE SHARE SUBSCRIBE Iphone 6s : http://amzn.to/2eyU8zi Gorilla Pod : http://amzn.to/2gAdVPq White Board : http://amzn.to/2euGJ7F Duster : http://amzn.to/2ev0qvX Feltip Markers : http://amzn.to/2eutbZC
Views: 1259 Ranji Raj
Overview of Data Mining course
 
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Overview of Data Mining course, course structure, outcomes, schedule, reference
Views: 276 kks RGUKT
Data warehouse Features Lecture in Hindi - DWDM Lectures in Hindi, English
 
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Data warehouse Features Lecture in Hindi - DWDM Lectures in Hindi, English Data warehouse Features – Subject Oriented, Integrated, Time Variant, Non-Volatile Data, Data Granularity Data Warehouse and Data Mining Lectures in Hindi
How to link PowerPoint to Excel for dynamic data updates?
 
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Sometimes you want to display live information in a PowerPoint presentation. Maybe you need to display scores or results in real time to people on a television screen. A manager needs to see production figures of a factory at his desk. People on the floor need to know their targets etc. This can be accomplished with data driven presentations. To display numbers and figures you don’t use a word processor but a spreadsheet like Microsoft Excel. There you can enter your raw data and make some simple or complex calculations. Of course you don’t want to display an Excel sheet on your message boards with its grid lines etc but you need presentation software like Microsoft PowerPoint. PowerPoint is the ideal software for presentations but it is static. There is a tool DataPoint available that allows you to create dynamic presentations with live data from Excel worksheets. Some people tend to copy and paste Excel objects in their PowerPoint but that is not done. It will even not update automatically over the network. You see the Excel grid lines in a presentation which is not professional looking. You can use the data only from the Excel worksheet but you do the formatting in your PowerPoint presentation. You can emphasize which text boxes are more important by setting a color, or a more important position on the slide with maybe arrows pointing to this value and some animation. PowerPoint, with its data from Excel, gives you more control! Let me show you how easily you can display live information from an Excel worksheet in a PowerPoint and update in real time. -------------------------------------------------------------- Download Free PowerPoint Digital Signage and other templates here: https://www.presentationpoint.com/templates/ Access our Free online course: "How to Use PowerPoint for Digital Signage" http://presentationpoint.usefedora.com/courses/how-to-use-powerpoint-for-digital-signage -------------------------------------------------------------- Connect with us on Social: Facebook: https://www.facebook.com/PresentationPoint Twitter: https://twitter.com/PresentationPnt YouTube: https://www.youtube.com/c/PresentationPointChannel LinkedIn: http://www.linkedin.com/company/3500848 Google+: https://plus.google.com/+Presentationpoint
Views: 88223 PresentationPoint
Data Mining & Business Intelligence | Tutorial #3 | Issues in Data Mining
 
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This video addresses the issues which are there involved in Data Mining system. Watch now! #RanjiRaj #DataMining #DMIssues Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj
Views: 2175 Ranji Raj
PDF Data Extraction and Automation 3.1
 
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Learn how to read and extract PDF data. Whether in native text format or scanned images, UiPath allows you to navigate, identify and use PDF data however you need. Read PDF. Read PDF with OCR.
Views: 110850 UiPath
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Warehousing | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial: 1. What Is The Need For BI? 2. What Is Data Warehousing? 3. Key Terminologies Related To DWH Architecture: a. OLTP Vs OLAP b. ETL c. Data Mart d. Metadata 4. DWH Architecture 5. Demo: Creating A DWH - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Intelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 191585 edureka!
1 - Introduction to Data warehouse and Data warehousing
 
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Short Introduction Video to understand, What is Data warehouse and Data warehousing? How it is different from Database? It also talks about properties of Data warehouse which are Subject Oriented, Integrated, Time Variant, Non Volatile ETL Tools: Talend Open Studio, Jaspersoft ETL, Ab initio, Informatica, Datastage, Clover ETL, Pentaho ETL, Kettle. #datawarehouse #ETL #DWH Business Intelligence tools: Oracle BI, Microsoft BI suite, Tableau, Qlik, Jaspersoft BI, Pentabo BI, Miscrostrategy, Tibco For more details visit: http://www.vikramtakkar.com/2015/08/what-is-datawarehouse-and.html Datawarehouse Playlist: https://www.youtube.com/playlist?list=PLJ4bGndMaa8FV7nrvKXeHCLRMmIXVCyOG
Views: 104576 Vikram Takkar
Data Warehouse Interview Questions And Answers | Data Warehouse Tutorial | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This Data Warehouse Interview Questions And Answers tutorial will help you prepare for Data Warehouse interviews. Watch the entire video to get an idea of the 30 most frequently asked questions in Data Warehouse interviews. - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Inelligence playlist here: https://goo.gl/DZEuZt. #DataWarehouseInterviewQuestions #DataWarehouseConcepts #DataWarehouseTutorial Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 78835 edureka!
EDW - Enterprise Data Warehouse
 
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Intro to powerpoint
Views: 8 Scott Bruce
Data Mining Classification - Basic Concepts
 
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Classification in Data Mining with classification algorithms. Explanation on classification algorithm the decision tree technique with Example.
Data pre processing – 1 Summarization and Cleaning Methods
 
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Project Name: e-Content generation and delivery management for student –Centric learning Project Investigator:Prof. D V L N Somayajulu
Views: 5228 Vidya-mitra
Lecture 48 — Dimensionality Reduction with SVD | 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. .
Introduction to Data Mining: Data Cleaning
 
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In this video we introduce Data Preprocessing, known as data cleaning, and the different strategies used to tackle it. -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 3600+ employees from over 742 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Learn more about Data Science Dojo here: https://hubs.ly/H0f8M6d0 See what our past attendees are saying here: https://hubs.ly/H0f8Ln10 -- 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: 7276 Data Science Dojo
What is Data Mining?
 
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NJIT School of Management professor Stephan P Kudyba describes what data mining is and how it is being used in the business world.
Views: 386870 YouTube NJIT
SSIS Tutorial For Beginners | SQL Server Integration Services (SSIS) | MSBI Training Video | Edureka
 
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This Edureka SSIS Tutorial video will help you learn the basics of MSBI. SSIS is a platform for data integration and workflow applications. This video covers data warehousing concepts which is used for data extraction, transformation and loading (ETL). It is ideal for both beginners and professionals who want to brush up their basics of MSBI. This Edureka training video provides knowledge on the following topics: 1. Why do we need data integration? 2. What is data integration? 3. Why SSIS? 4. What is SSIS? 5. ETL process 6. Data Warehousing 7. Installation 8. What is SSIS Package? 9. Demo Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Microsoft BI playlist here: https://goo.gl/Vo6Klo #SSIS #SSISTutorial #MicrosoftBI #MicrosoftBItutorial #MicrosoftBIcourse How it Works? 1. This is a 30 Hours of Online Live Instructor-Led Classes. Weekend Class : 10 sessions of 3 hours each. Weekday Class : 15 sessions of 2 hours each. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Microsoft BI Certification Course is designed to provide insights on different tools in Microsoft BI Suite (SQL Server Integration Services, SQL Server Analysis Services, SQL Server Reporting Services). Get expertise in SSIS , SSAS & SSRS concepts and master them. The course will give you the practical knowledge on Data Warehouse concepts and how these tools help in developing a robust end-to-end BI solution using the Microsoft BI Suite. Who should go for this course? Microsoft BI Certification Course at Edureka is designed for professionals aspiring to make a career in Business Intelligence. Software or Analytics professionals having background/experience of any RDBMS, ETL, OLAP or reporting tools are the key beneficiaries of this MSBI course. You can check a blog related to Microsoft BI – Why You Need It For A Better Business Intelligence Career!! Also, once your Microsoft BI training is over, you can check the Microsoft Business Intelligence Interview Questions related edureka blog. Why learn Microsoft BI ? As we move from experience and intuition based decision making to actual decision making, it is increasingly important to capture data and store it in a way that allows us to make smarter decisions. This is where Data warehouse/Business Intelligence comes into picture. There is a huge demand for Business Intelligence professionals and this course acts as a foundation which opens the door to a variety of opportunities in Business Intelligence space. Though there are many vendors providing BI tools, very few of them provide end to end BI suite and huge customer base. Microsoft stands as leader with its user-friendly and cost effective Business Intelligence suite helping customers to get a 360 degree view of their businesses. Please write back to us at [email protected] or call us at +918880862004 or 18002759730 for more information. Website: https://www.edureka.co/microsoft-bi Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Amit Vij, HRSSC HRIS Senior Advisor at DLA Piper, says "I am not a big fan of online courses and also opted for class room based training sessions in past. Out of surprise, I had a WoW factor when I attended first session of my MSBI course with Edureka. Presentation - Check, Faculty - Check, Voice Clarity - Check, Course Content - Check, Course Schedule and Breaks - Check, Revisting Past Modules - Awesome with a big check. I like the way classes were organised and faculty was far above beyond expectations. I will recommend Edureka to everyone and will personally revisit them for my future learnings."
Views: 122188 edureka!
REST API concepts and examples
 
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This video introduces the viewer to some API concepts by making example calls to Facebook's Graph API, Google Maps' API, Instagram's Media Search API, and Twitter's Status Update API. /********** VIDEO LINKS **********/ Youtube's Facebook Page via the Facebook Graph API http://graph.facebook.com/youtube Same thing, this time with filters https://graph.facebook.com/youtube?fields=id,name,likes Google Maps Geocode API call for the city of Chicago http://maps.googleapis.com/maps/api/geocode/json?address=Chicago Apigee Instagram API console https://apigee.com/console/instagram HTTP Request Methods http://en.wikipedia.org/wiki/Hypertext_Transfer_Protocol#Request_methods Postman Chrome Extension https://chrome.google.com/webstore/detail/postman-rest-client/fdmmgilgnpjigdojojpjoooidkmcomcm?hl=en Twitter's Status Update documentation. https://dev.twitter.com/docs/api/1.1/post/statuses/update
Views: 2815639 WebConcepts
[Коллоквиум]: Rough sets: A tool for qualitative knowledge discovery
 
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Rough set theory (RST) was introduced in the early 1980s by Z. Pawlak (1982) and has become a well researched tool for knowledge discovery. The basic assumption of RST is that information is presented and perceived up to a certain granularity: "The information about a decision is usually vague because of uncertainty and imprecision coming from many sources [. . . ] Vagueness may be caused by granularity of representation of the information. Granularity may introduce an ambiguity to explanation or prescription based on vague information" (Pawlak and Słowin ́ski, 1993). In contrast to other machine learning or statistical methods, the original rough set approach uses only the information presented by the data itself and does not rely on outside distributional or other parameters. RST relies only on the principle of indifference and the nominal scale assumption. It has been applied in many fields, most recently in the investigation of complex adaptive systems, interactive granular computing, and big data analysis (Skowron et al., 2016). In my talk I will present the basic concepts of RST as well as non–parametric methods for feature reduction, data filtering, significance testing and model selection.
Views: 2325 ФКН ВШЭ
Dimensionality Reduction: Principal Components Analysis, Part 1
 
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Data Science for Biologists Dimensionality Reduction: Principal Components Analysis Part 1 Course Website: data4bio.com Instructors: Nathan Kutz: faculty.washington.edu/kutz Bing Brunton: faculty.washington.edu/bbrunton Steve Brunton: faculty.washington.edu/sbrunton
Views: 64975 Data4Bio
Seadrill are mining the benefits of Azure big data.
 
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Seadrill are revolutionising how data is collected, visualised and utilised in the deep-water drilling industry.
Views: 2182 Microsoft UK
Towards Ontology Based Data Access for Statoil. Part 1: Introduction
 
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Ontology Based Data Access (OBDA) is a prominent approach to provide end-users with high-level access to data via an ontology that is 'connected' to the data via mappings. State-of-the-art OBDA systems, however, suffer from limitations restricting their applicability in industry. In particular, development of necessary prerequisites to deploy an OBDA system, i.e., ontologies and mappings, as well as end-user oriented query interfaces, are poorly addressed. Moreover, solutions often focus on separate critical components of OBDA systems, while, to the best of our knowledge, there is no end-to-end OBDA solution. The Optique platform provides an integrated end-to-end OBDA system that addresses a number of practical challenges including support for development of deployment prerequisites and user-oriented query interfaces. During the demonstration one can try the platform with preconfigured scenarios from the petroleum industry and music domain, and try its end-to-end functionality: from deployment to query answering. In the first part we provide a general description of the OBDA approach in general and our system particularly.
Views: 800 Optique Project
Session 5: Part 1 MongoDB and Data Mining Examples
 
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For each week, relevant content covered will be placed on this YouTube channel
Views: 143 Mark Altaweel
Crowdsourcing based Description of Urban Emergency Events using Social Media Big Data
 
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Title: Crowdsourcing based Description of Urban Emergency Events using Social Media Big Data Domain: Data Mining Key Features: 1. Crowdsourcing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles, buildings, and human. Especially, nowadays, no countries, no communities, and no person are immune to urban emergency events. 2. Detection about urban emergency events, e.g., fires, storms, traffic jams is of great importance to protect the security of humans. Recently, social media feeds are rapidly emerging as a novel platform for providing and dissemination of information that is often geographic. 3. In this paper, in order to detect and describe the real time urban emergency event, the 5W (What, Where, When, Who, and Why) model is proposed. Firstly, users of social media are set as the target of crowd sourcing. Secondly, the spatial and temporal information from the social media are extracted to detect the real time event. Thirdly, a GIS based annotation of the detected urban emergency event is shown. 4. The proposed method is evaluated with extensive case studies based on real urban emergency events. The results show the accuracy and efficiency of the proposed method. 5. The proposed model is based on crowdsourcing, which uses the real time nature of Weibo users. The proposed model is applied into the emergency management field, which can provide useful information to analyze and resist urban emergency events. For more details contact: E-Mail: [email protected] Buy Whole Project Kit for Rs 5000%. Project Kit: • 1 Review PPT • 2nd Review PPT • Full Coding with described algorithm • Video File • Full Document Note: *For bull purchase of projects and for outsourcing in various domains such as Java, .Net, .PHP, NS2, Matlab, Android, Embedded, Bio-Medical, Electrical, Robotic etc. contact us. *Contact for Real Time Projects, Web Development and Web Hosting services. *Comment and share on this video and win exciting developed projects for free of cost. Search Terms: 1. 2017 ieee projects 2. latest ieee projects in java 3. latest ieee projects in data mining 4. 2017 – 2018 data mining projects 5. 2017 – 2018 best project center in Chennai 6. best guided ieee project center in Chennai 7. 2017 – 2018 ieee titles 8. 2017 – 2018 base paper 9. 2017 – 2018 java projects in Chennai, Coimbatore, Bangalore, and Mysore 10. time table generation projects 11. instruction detection projects in data mining, network security 12. 2017 – 2018 data mining weka projects 13. 2017 – 2018 b.e projects 14. 2017 – 2018 m.e projects 15. 2017 – 2018 final year projects 16. affordable final year projects 17. latest final year projects 18. best project center in Chennai, Coimbatore, Bangalore, and Mysore 19. 2017 Best ieee project titles 20. best projects in java domain 21. free ieee project in Chennai, Coimbatore, Bangalore, and Mysore 22. 2017 – 2018 ieee base paper free download 23. 2017 – 2018 ieee titles free download 24. best ieee projects in affordable cost 25. ieee projects free download 26. 2017 data mining projects 27. 2017 ieee projects on data mining 28. 2017 final year data mining projects 29. 2017 data mining projects for b.e 30. 2017 data mining projects for m.e 31. 2017 latest data mining projects 32. latest data mining projects 33. latest data mining projects in java 34. data mining projects in weka tool 35. data mining in intrusion detection system 36. intrusion detection system using data mining 37. intrusion detection system using data mining ppt 38. intrusion detection system using data mining technique 39. data mining approaches for intrusion detection 40. data mining in ranking system using weka tool 41. data mining projects using weka 42. data mining in bioinformatics using weka 43. data mining using weka tool 44. data mining tool weka tutorial 45. data mining abstract 46. data mining base paper 47. data mining research papers 2017 - 2018 48. 2017 - 2018 data mining research papers 49. 2017 data mining research papers 50. data mining IEEE Projects 52. data mining and text mining ieee projects 53. 2017 text mining ieee projects 54. text mining ieee projects 55. ieee projects in web mining 56. 2017 web mining projects 57. 2017 web mining ieee projects 58. 2017 data mining projects with source code 59. 2017 data mining projects for final year students 60. 2017 data mining projects in java 61. 2017 data mining projects for students
Data Warehouse Concepts | Data Warehouse Tutorial | Data Warehouse Architecture | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This tutorial on data warehouse concepts will tell you everything you need to know in performing data warehousing and business intelligence. The various data warehouse concepts explained in this video are: 1. What Is Data Warehousing? 2. Data Warehousing Concepts: 3. OLAP (On-Line Analytical Processing) 4. Types Of OLAP Cubes 5. Dimensions, Facts & Measures 6. Data Warehouse Schema - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Inelligence playlist here: https://goo.gl/DZEuZt. #DataWarehousing #DataWarehouseTutorial #DataWarehouseTraining #DataWarehouseConcepts Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - Please write back to us at [email protected] or call us at +91 90660 20866 for more information. Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 42983 edureka!
Data Mining with Big Data IEEE DOT NET 2014
 
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Frontline offers Final Year IEEE Projects. Get the abstract, project source code, documentation ,ppt and UML Diagrams. Online Demo and Training Sessions available. Frontline India visit us at frontl.in Call +91 7200 247 247 or mail us at [email protected] Online Training Sessions available
knime hadoop integration Data Analytics projects
 
06:37
Contact Best Hadoop Projects Visit us: http://hadoopproject.com/
Views: 325 Hadoop Solutions
Towards Effective Bug Triage with Software Data Reduction Techniques | Final Year Projects 2016
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/lGybbe Chat Now @ http://goo.gl/snglrO Visit Our Channel: http://www.youtube.com/clickmyproject Mail Us: [email protected]
Views: 518 Clickmyproject
Excel and DataTables Automation 3.3
 
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Learn how UiPath operates with Excel and Data Tables: - Excel application scope - Opening a workbook - access modes - Read and write range - Output datatable Watch a practical example of how to sort data in an Excel file and iterate through all rows.
Views: 180575 UiPath
How To Install KNIME Analytics Platform on Windows, Installation and Administration Guide
 
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This video is an introduction of KNIME. KNIME is an open source platform for data analysis, predictive KNIME, the open platform for your data. ... Course for KNIME Analytics Platform, Berlin - November 2017. 15 Nov 2017. Course for KNIME Server, Berlin KNIME (pronounced /naɪm/), the Konstanz Information Miner, is an open source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface allows assembly of nodes for data preprocessing (ETL: Extraction, Transformation, Loading), for modeling and data analysis and visualization without, or with only minimal, programming. To some extent KNIME can be considered as an SAS alternative. Since 2006, KNIME has been used in pharmaceutical research,[2] but is also used in other areas like CRM customer data analysis, business intelligence and financial data analysis. History: The Development of KNIME was started January 2004 by a team of software engineers at University of Konstanz as a proprietary product. The original developer team headed by Michael Berthold came from a company in Silicon Valley providing software for the pharmaceutical industry. The initial goal was to create a modular, highly scalable and open data processing platform which allowed for the easy integration of different data loading, processing, transformation, analysis and visual exploration modules without the focus on any particular application area. The platform was intended to be a collaboration and research platform and should also serve as an integration platform for various other data analysis projects. In 2006 the first version of KNIME was released and several pharmaceutical companies started using KNIME and a number of life science software vendors began integrating their tools into KNIME. Later that year, after an article in the German magazine c't users from a number of other areas[9][10] joined ship. As of 2012, KNIME is in use by over 15,000 actual users (i.e. not counting downloads but users regularly retrieving updates when they become available) not only in the life sciences but also at banks, publishers, car manufacturer, telcos, consulting firms, and various other industries but also at a large number of research groups worldwide. Latest updates to KNIME Server and KNIME Big Data Extensions, provide support for Apache Spark 2.0. Internals KNIME allows users to visually create data flows (or pipelines), selectively execute some or all analysis steps, and later inspect the results, models, and interactive views. KNIME is written in Java and based on Eclipse and makes use of its extension mechanism to add plugins providing additional functionality. The core version already includes hundreds of modules for data integration (file I/O, database nodes supporting all common database management systems through JDBC), data transformation (filter, converter, combiner) as well as the commonly used methods of statistics, data mining, analysis and text analytics. Visualization supports with the free Report Designer extension. KNIME workflows can be used as data sets to create report templates that can be exported to document formats like doc, ppt, xls, pdf and others. Other capabilities of KNIME are: KNIMEs core-architecture allows processing of large data volumes that are only limited by the available hard disk space (most other open source data analysis tools work in main memory and are therefore limited to the available RAM). E.g. KNIME allows analysis of 300 million customer addresses, 20 million cell images and 10 million molecular structures. Additional plugins allows the integration of methods for Text mining, Image mining, as well as time series analysis. KNIME integrates various other open-source projects, e.g. machine learning algorithms from Weka, the statistics package R project, as well as LIBSVM, JFreeChart, ImageJ, and the Chemistry Development Kit. KNIME is implemented in Java but also allows for wrappers calling other code in addition to providing nodes that allow running Java, Python, Perl and other code fragments. also a ML tool is WEKA(A Data Mining Tool)
Views: 171 BaD Gaming
Applications of AI in IoT | Applications of Big Data in IoT | IoT Future | IoT Career
 
01:11:02
This webinar explains the below points: - Introduction to IoT - Big Data Introduction - Artificial Intelligence Introduction - Big Data & IoT Case Study - Artificial Intelligence & IoT Case Study - Career Path in IoT Space About the Speaker: The Speaker is Vijayakeerthi Jayakumar. He has 7+ years of industry experience in analytics & data science stream. He has rich experience in building machine learning based solutions to create business impact. Strategic & Performance oriented executive focused on mission and goals with proven track record in handling business requirements & complex problem solving using statistical techniques. Avid learner of new technologies and open-minded exploration attitude to build new skillsets. Data-driven consulting & product development focusing on ROI across multiple functions such as Marketing, Operations, Finance. About us: HackerEarth is building the largest hub of programmers to help them practice and improve their programming skills. At HackerEarth, programmers: 1. Solve problems on Algorithms, DS, ML etc(https://goo.gl/6G4NjT). 2. Participate in coding contests(https://goo.gl/plOmbn) 3. Participate in hackathons(https://goo.gl/btD3D2) Subscribe Our Channel For More Updates : https://goo.gl/suzeTB For More Updates, Please follow us on : Facebook : https://goo.gl/40iEqB Twitter : https://goo.gl/LcTAsM LinkedIn : https://goo.gl/iQCgJh Blog : https://goo.gl/9yOzvG
Views: 892 HackerEarth
salesforce ≠ Data Warehouse
 
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Often a transaction system can be confused with data integration and information delivery. This is partially because operational data can be retrieved from these systems. This video clarifies the differences between a data warehouse and a transaction system by sharing a recent example with salesforce.com To Talk with a Specialist go to: http://www.intricity.com/intricity101/
Views: 12564 Intricity101
text mining and olap
 
01:30
Views: 226 rajan10000
IEEE 2015 PROJECTS-Towards Effective Bug Triage with Software Data Reduction Techniques
 
02:43
S3 technologies, 43, North Masi street, Phone: 0452-4373398 Simmakkal, Madurai Visit: www.s3techindia.com Mail: [email protected] visit:s3studentproject.blogspot.in
Views: 630 S3 TECHNOLOGIES
Real Time Data Warehousing by Anas Khalid
 
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Hello, This is my brief explanation on how data warehousing can benefit real time data applications and its some of its real world applications. If you have any queries then feel free to contact me at [email protected] :)
Views: 14 anas khalid
Big Data in Agriculture | agriculture big data | Application of big data analytics in agriculture
 
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Big Data in Agriculture | agriculture big data | application of big data analytics in agriculture Welcome to this video on Big Data in Agriculture . Our facebook page http://www.facebook.com/learningseveryday blog www.ethtimes1.blogspot.com As all of us know the role of big data in every field of life. Big data is moving into agriculture in a big way. Sensors on fields and crops are starting to provide literally granular data points on soil conditions, as well as detailed info on wind, fertilizer requirements, water availability and pest infestations. Just like how it has improved business operations in many industries, the big data revolution has made its way into the farming industry and modernized it at a pace we've never seen before. Farmers and other stakeholders have started seeing benefits such as reduction in fertilizer, cost savings, yield optimization, and more. Thanks for watching this video on big data in agriculture. -~-~~-~~~-~~-~- Please watch: "what is flow chart | symbols of flowchart explained in hindi" https://www.youtube.com/watch?v=k2I8gp1NGGU -~-~~-~~~-~~-~-
Views: 935 Learning Everyday
A Review on Mining Students’ Data for Performance Prediction  | Final Year Projects 2016 - 2017
 
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Including Packages ======================= * Base Paper * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Readme File * Addons * Video Tutorials * Supporting Softwares Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * * Remote Connectivity * * Code Customization ** * Document Customization ** * Live Chat Support * Toll Free Support * Call Us:+91 967-774-8277, +91 967-775-1577, +91 958-553-3547 Shop Now @ http://clickmyproject.com Get Discount @ https://goo.gl/dhBA4M Chat Now @ http://goo.gl/snglrO Visit Our Channel: https://www.youtube.com/user/clickmyproject Mail Us: [email protected]
Views: 560 Clickmyproject
Association Rule Mining in Hadoop.webm
 
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Demo For Project QFP By Team Skies for the CS568 DataMining course in IITG Project is done in hadoop framework and association rule mining algorithm is implemented
Views: 889 Santhosh Sriram

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