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

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

General

• Visualization of multidimensional data using Andrews charts
• Microsoft buys Revolution Analytics
• Top SlideShare presentations on Big Data - an updated version of the rating of the most popular SlideShare presentations on Big Data with a little analytics from KDnuggets.com.
• Data Scientist: 5 Basic Skills
  
• 15 great data visualizations
• Researchers have shown a machine learning network for groups of distributed devices.
• 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
• Building a recommendation system (part 1)
• A few words about artificial neural networks and deep learning
• Build 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 Case-Based Analysis
• Deep Learning Visualization is a great article that will help you better understand how Deep Learning works.
• Clustering using the k-means method: you have to pay for everything - a small interesting article, in which the author discusses the intricacies of the clustering algorithm using the k-means method.
• A bit about convolutional neural networks
• Deep immersion in recurrent neural networks
• An overview of the Kernel PCA algorithm
• Machine learning for face recognition is a good example of using machine learning algorithms for face recognition using the scikit-learn library for the Python programming language.
• Text Analysis for Newbies: Document Classification
• Go convolutional neural network learning
• Model performance (Part 2) - in this article, Analytics blog author Vydhya will continue the topic of assessing the performance of the predictive model.
• An introduction to caretEnsemble is a useful article about the caretEnsemble library, which 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 simple language - a good short description of decision trees from the blog Analytics Vidhya.
• Data Analysis in Python - useful code examples for data analysis using the Python programming language.
• Jetpack: Docker machine learning tools
• Major developer errors when using Python to analyze big data
• An example of using Random Forest and boosting using MLlib
• A set of useful tricks for Pandas is a small list of useful code examples for the Pandas library for the Python programming language.

Machine learning competitions

• How to get started in Kaggle: a guide for beginners in Data Science
• New machine learning competition “How much did it rain?” - a few days ago, a new machine learning competition “How much did it rain?” Started at Kaggle

Online courses, educational materials and literature

• Beginning of the online course Mining Massive Datasets from Stanford University - January 31, the second session of the online course Mining Massive Datasets from Stanford University will begin on Coursera
• Book Review: Advanced Analytics with Apache Spark
• Free ebook: H2O and R is a free book about the H2O machine learning platform and its use with the R programming language.

Video

• Introduction to Random Forest by Dr. Nando de Freitas - this post presents a lecture on Dr. Machine’s Random Random Forest Learning Algorithm. Nando de Freitas (Full-time Professor at Oxford).

Data engineering

• Surus: a new open source project for analyzing data in Hadoop from Netflix

Reviews

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

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