Review of the most interesting materials on data analysis and machine learning №30 (January 5 - 11, 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

• Data Science Cheat Sheets are a good list of various cheat sheets for Data Science.
• Perspectives Data Science is an interesting question and answer session from the Microsoft Technet SQL Server blog with two Data Scientist from Microsoft.
• How to choose a project for your Data Science portfolio
• Don’t worry, Python doesn’t replace R
• The main trends in the labor market in the field of Big Data, which should be paid attention in 2015
• 24 useful resources on Data Science - a good list of resources that will help keep abreast of the latest developments in Data Science.
• 9 skills that will be needed in 2015 to work in the field of Big Data
• 9 tips to help make Data Mining more efficient

Theory and algorithms of machine learning, code examples

• Trivium Theory of Measurement
• Analyzing data from smartphone sensors using R and BreakoutDetection library
• The new version of the library Caret - a new version of the popular library Caret for machine learning for the R programming language appeared in CRAN. This short post describes the main innovations of this version.
• Python Libraries for Data Analysis
• What is scikit-learn? - a brief description of the popular machine learning library scikit-learn for the Python programming language from the author of the blog Analytics Vidhya.
• Machine learning with wearable devices using scikit-learn and Python
• Identifying anomalies in time series - an article from Twitter's blog about an interesting new library for the R programming language with the open source code AnomalyDetection for identifying anomalies in time series.
• Using the AnomalyDetection library on Wikipedia Page View Data is a continuation of the topic of using the AnomalyDetection library from Twitter.
• How does linear regression work? - simple language about linear regression.
• Visually about neural networks - a small article with an illustrated description of the work of neural networks.
• Random separation of data into test and training sets: this may not be enough
• Image processing and feature selection using Python
• An example of the visualization of the Kalman filter using R

Machine learning competitions

• BudgetApps - First All-Russian Open Financial Data Competition
• Machine Learning Metrics: ROC and AUC
• Winner Report "Getting a Handel on Data Science" on Kaggle InClass
• AI competition for Angry Birds

Online courses, educational materials and literature

• The beginning of the new online course “Artificial Intelligence Planning” - at the beginning of next week, the Coursera will begin the course “Artificial Intelligence Planning” presented by The University of Edinburgh.
• Online Course “Image and video processing” at Coursera - On January 5, a new session of the popular online course “Image and Video Processing: From Mars to Hollywood with a stop at the hospital” from Duke University began at the Coursera.
• The “Computational Methods for Data Analysis” course started - the next session of the rather popular “Computational Methods for Data Analysis” course from the University of Washinton began a few days ago at Coursera.
• Online course "Data Analysis and Visualization Using R"
• Book: "Introduction to Probability, Statistics, and Random Processes"
• Book: "Data Driven: Creating a Data Culture"

Video

• The best performances of Strata + Hadoop World - this post contains a list of the best presentations from the Strata + Hadoop World conferences.

Data engineering

• New new thing (The new new thing)
• Big Data on your computer: How to install Hadoop 2.6.0
• Spark SQL Data Sources API: Unified Data Access on the Apache Spark Platform
• Free ebook: Field Guide To Hadoop
• Apache Samza: LinkedIn streaming processing

Reviews

• Interesting from the world of R (January 5-11, 2015)
• Weekly Digest from DataScienceCentral (January 12)
• The best materials for the week from KDnuggets.com (December 28 - January 3)
• Digest of the best resources from DataScienceCentral January 6)
• Data Science News from MyDataMine.com (January 8)
• Big Data News from MyDataMine.com (January 9)
• Weekly collection of the best materials from R1Soft (January 9)
• The best resources for the week from Data Elixir (# 17)
• The most interesting materials from Freakonometrics №201
• The most interesting materials from Freakonometrics # 202
• The most interesting materials on High Scalability (January 9)

Previous release: Review of the most interesting materials on data analysis and machine learning №29 (December 29, 2014 - January 4, 2015)