
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
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)