Overview of the most interesting materials on data analysis and machine learning No. 32 (January 19 - 25, 2015)

I present to you the next issue of a review of the most interesting materials on the topic of data analysis and machine learning.

General

•   Visualizing multidimensional data with Andrews charts
•   Microsoft buys Revolution Analytics
•  Best SlideShare Big Data Presentations - An updated version of the ranking of SlideShare's most popular Big Data presentations with some analytics from KDnuggets.com.
•  Data Scientist: 5 Essential Skills
  
•  15 great data visualizations
•  Researchers reveal machine learning network for distributed device groups
•  Computers learn how to treat cancer and diabetes by playing atari and poker
•  The history of the development of computer vision algorithms over the past 20 years
•   Construction of a recommender system (part 1)
•  A Few Words About Artificial Neural Networks and Deep Learning
•  Building scalable machine learning algorithms

Theory and algorithms of machine learning, code examples

•    Introduction to scikit-learn - this post provides an overview of the scikit-learn machine learning library.
•    Data tidying: Preparing data sets for analysis using case studies
•   Visualizing Deep Learning is a great article to help you better understand how Deep Learning works.
•  Clustering by the k-means method: you have to pay for everything - a small curious article in which the author discusses the intricacies of the k-means clustering algorithm (k-means).
•  A bit about convolutional neural networks
•   Deep immersion in recurrent neural networks
•   Kernel PCA Algorithm Overview
•   Machine learning for face recognition - a good example of the use of machine learning algorithms for face recognition using scikit-learn library for Python programming language.
•   Text Analysis for Beginners: Document Classification
•   Convolutional neural network training game Go
•  Model Performance (Part 2) - in this article, the author of the blog Analytics Vydhya will continue the topic of evaluating the performance of a predictive model.
•   An introduction to caretEnsemble is a useful article on the caretEnsemble library that allows you to apply algorithmic compositions (Ensemble Methods) to models from the popular caret machine learning library for the programming language R.
•   About decision trees in plain language is a good short description of decision trees from the Vidhya Analytics blog.
•   Data Analysis in Python - Useful code examples for analyzing data using the Python programming language.
•  Jetpack: Machine Learning Tools at Docker
•   Major developer mistakes when using Python to analyze big data
•   An example of using Random Forest and boosting with MLlib
•   The Pandas Toolkit is a short list of useful code examples for the Pandas library for the Python programming language.

Machine Learning Competitions

•   Getting Started at Kaggle: A Guide for Beginners in Data Science
•  New Machine Learning Competition “How much did it rain?” - a few days ago at Kaggle a new machine learning competition “How much did it rain?” Began

Online courses, training materials and literature

•   Start of Stanford University's Mining Massive Datasets online course - On January 31, Coursera will begin the second session of Stanford University’s Mining Massive Datasets online course.
•   Book Review: Advanced Analytics with Apache Spark
•    Free e-book: H2O and R - a free book about the H2O machine learning platform and its use with the programming language R.

Videos

•     Introduction to Random Forest by Dr. Nando de Freitas - in this post a lecture on the popular machine learning algorithm Random Forest from Dr. Nando de Freitas (Adjunct Professor at UBC Computer Science, Full-time Professor at Oxford).

Data engineering

•  Surus: Netflix's new open source data analysis project in Hadoop

Reviews

•  Interesting from the world of R (January 19-25, 2015)
•  DataScienceCentral Weekly Digest (January 26)
•  Digest of the best resources from DataScienceCentral (January 23)
•  Best Content of the Week from KDnuggets.com (January 11-17)
•  Data Science News from MyDataMine.com (January 22)
•  Best Resources of the Week from Data Elixir (No.19)
•  The weekly collection of the best materials from R1Soft (January 23)
•  The most interesting materials on High Scalability (January 23)

Previous issue:  Overview of the most interesting materials on data analysis and machine learning No. 31 (January 12 - 18, 2015)