Overview of the most interesting materials on data analysis and machine learning No. 36 (February 16 - 22, 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

•   Seventh annual Microsoft Research Summer School. This time about machine learning and intelligence
•   IBM Watson for Oncology: helping the cognitive system fight cancer
•  Artificial intelligence that can understand what the video is about
•   Russian-language resources on statistics, machine learning, R
•  Infographics: The History of Data Science
•  Microsoft Strengthens Python and Linux Positions in Its New Big Data Tools
•   Getting started and developing in the field of machine learning is a good motivating article from the author of the blog MachineLearningMastery.
•  Currently Apache Spark looks like the future of Big Data
•  Deeplearning4j: Deep Learning Library for Java
•  Data Science: List of Active Blogs
•  Microsoft announced the availability of the Azure Machine Learning platform
•  How Pinterest Fights Spam
•  Google has made available a library for working with MapReduce using C / C ++
•  Pintereset: Real-time analytics - Pinterest engineers review their real-time analytics system architecture.
•  What to do during model training runs are some interesting ideas from the author of the MachineLearningMastery blog about what to do during pauses that may occur during the start of model training processes in machine learning tasks.
•  Channel 9 has developed a recommendation API for Azure ML

Theory and algorithms of machine learning, code examples

•    Machine Learning - 1. Correlation and regression. Example: site visitors conversion
  
•    Introduction to Apache Spark
•   Overview of Audio Analytics Algorithms
•   Billiard bot: the history of creation
•  Neural networks in Azure ML - introduction to Net #
•    Introduction to Bayesian Networks Using R
•   Basics of Parallelization Using the R Programming Language
•   Receiving data from Arduino sensors using the R programming language
•   Kayak: a library for working with deep neural networks
•  An example of hierarchical clustering - a visualized example of a hierarchical clustering created using the R programming language and the Shiny visualization library.
•   A series of lessons in machine learning and natural language processing. Lesson 3: Bayes Theorem

Machine Learning Competitions

•  Machine Learning Contest: Microsoft Malware Classification Challenge (BIG 2015)
•  Machine Learning Contest: March Machine Learning Mania 2015

Online courses, training materials and literature

•   Introduction to the course "Image and Video Analysis". Lectures from Yandex
•   Online Course: D003x.1: Applications of Linear Algebra Part 1
•   Model Building and Validation - Advanced Techniques for Analyzing Data Online Course
•   Book Review: Data Mining for Managers
•   Interview with the author of R Machine Learning Essentials

Videos, podcasts

•   Apache Spark - SDK for all Big Data platforms - an interesting report on Apache Spark. In this presentation, Pat McDonough talks about the development of Apache Spark and the possibility of using this product in the field of data processing and analysis.
•   Apache Spark DataFrame for scaling Data Science tasks - video from the recent mitap in addition to news that Apache Spark 1.3 will introduce a new option to use DataFrame. Actually in this video Reynold Xin will talk about this new functionality in Apache Spark.
•   Introduction to Deep Learning Using Python

Data engineering

•  Microsoft makes Apache Storm publicly available on its Azure cloud platform
•  Recent Apache Spark Performance Improvements - Reynold Xin talks about the latest significant Apache Spark performance improvements.
•  Announcement of DataFrame in Apache Spark - in Apache Spark version 1.3 it will be possible to use DataFrame, this article will talk about the details of the implementation and use of DataFrame in Apache Spark.
•  Extending analytics capabilities in MemSQL with Apache Spark

Reviews

•   Interesting from the world of R (February 9-15, 2015)
•  Best Content of the Week from KDnuggets.com (February 8-14)
•  Data Science News from MyDataMine.com (February 21)
•  Big Data News from MyDataMine.com (February 18)
•  DataScienceCentral Weekly Digest (February 23)
•  DataScienceCentral Weekly Digest (February 16)
•  Best Resources of the Week from Data Elixir (No.23)
•  The weekly collection of the best materials from R1Soft (February 20)
•  The most interesting materials on High Scalability (February 20)

Previous issue:  Overview of the most interesting materials on data analysis and machine learning No. 35 (February 9 - 15, 2015)