Tag: Classification

Feed: Featured Posts - Hadoop360 Author: Andrei Macsin Subscribe to our Newsletter Guest blog post by Vincent Granville Originally posted here, but this version here is up-to-date. We blended together the best of the best resources posted recently on DSC. It would be great to organize them by category, but for now they are organized by date. This is very useful too, since you are likely to have seen old entries already, and can focus on more recent stuff. Starred entries have interesting charts.  May 6, 2016 Linux Data Science Virtual Machine  Deep Learning for Beginners  Google BigQuery Public Datasets  How to Remove ... Read More

Feed: New Books and Journals Discussions - AnalyticBridge Author: Emmanuelle Rieuf Master machine learning techniques with R to deliver insights for complex projects About This Book Get to grips with the application of Machine Learning methods using an extensive set of R packages Understand the benefits and potential pitfalls of using machine learning methods Implement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system Who This Book Is For If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for ... Read More

Feed: New Books and Journals Discussions - AnalyticBridge Author: Emmanuelle Rieuf Books about the R programming language fall in different categories: Learning R Reference books for the professional R programmer Books about data science or visualization, using R to illustrate the concepts Books are a great way to learn a new programming language. Code samples is another great tool to start learning R, especially if you already use a different programming language. You might also want to check our DSC articles about R: they also include cheat sheets. If you are unsure about learning R, read about R versus Python. Example of chart produced with R ... Read More

Feed: New Books and Journals Discussions - AnalyticBridge Author: Emmanuelle Rieuf From Algorithms to Z-Scores:Probabilistic and Statistical Modeling in Computer Science. By Norm Matloff, University of California, Davis.  Click here to read the book (PDF document, 520 pages). I guess it will become a classic on the subject, for students learning traditional statistics. Contents 1 Time Waste Versus Empowerment 1 2 Basic Probability Models 3 2.1 ALOHA Network Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.2 The Crucial Notion ... Read More

Feed: Featured Posts - DataViz Author: Andrei Macsin Guest blog post by Irina Papuc Machine Learning (ML) is coming into its own, with a growing recognition that ML can play a key role in a wide range of critical applications, such as data mining, natural language processing, image recognition, and expert systems. ML provides potential solutions in all these domains and more, and is set to be a pillar of our future civilization. The supply of able ML designers has yet to catch up to this demand. A major reason for this is that ML is just plain tricky. This tutorial ... Read More

Feed: Featured Blog Posts - Data Science Central Author: Emmanuelle Rieuf Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. After discussing ... Read More

Feed: Featured Blog Posts - Data Science Central Author: William Vorhies Summary:  Which of these terms means the same thing:  AI, Deep Learning, Machine Learning?  Are you sure?  While there’s overlap none of these is a complete subset of the others and none completely explains the others. Take this quiz. Which of the following are substantially the same things? A. AI B. Deep Learning C.  Machine Learning (Select your answer) 1.  A and B 2.  B and C 3.  A and C 4.  All of the above. For as precise a profession as we data scientists purport to be we ... Read More

Feed: Resources Discussions - Data Science Central Author: Vincent Granville The following is a selection of featured articles that were posted in our previous weekly digests, in short, the best of the best on DSC. Single-starred articles are written by external/guest bloggers. Older popular articles are being added regularly, so please check out this page once a week! Our upcoming book on data science 2.0 (or data science automation or data science handbook or the little data science book, not sure yet about the title) will be based on some of these (edited and revised) articles: these articles are double-starred ... Read More

Feed: Resources Discussions - Data Science Central Author: Vincent Granville Here is selection containing both external and internal papers, focusing on various technical aspects of data science and big data. Feel free to add your favorites. Complex Open Text Analysis: Source: Avinash Kaushik External Papers Bigtable: A Distributed Storage System for Structured Data A Few Useful Things to Know about Machine Learning Random Forests A Relational Model of Data for Large Shared Data Banks Map-Reduce for Machine Learning on Multicore Pasting Small Votes for Classification in Large Databases and On-Line Recommendations Item-to-Item Collaborative Filtering Recursive Deep Models for Semantic Compositionality ... Read More

Feed: Featured Blog Posts - Data Science Central Author: William Vorhies Summary:  The most important developments in Deep Learning and AI in the last year may not be technical at all, but rather a major change in business model.  In the space of about six months all the majors have made their Deep Learning IP open source, hoping to gain on the competition from the power of the broader developer base and wide adoption.   To say that the last year has been big for Deep Learning is an understatement.  There have been some spectacular technical innovations like Microsoft winning ... Read More