Overview of the most interesting materials on data analysis and machine learning No. 1 (June 9 - 16, 2014)

This issue of the digest of the most interesting materials on the topic of data analysis contains a lot of articles that examine the theoretical aspects of issues related to Data Science. There are several articles that will be of interest to beginners. Links to a series of interesting articles about working with data schemes in MongoDb are also provided. There are several references to materials that address the important issue of overfitting in machine learning. Some articles are devoted to literature recommended for reading for those who are interested in the topic of data analysis.

Articles

• References for the summer  [EN]
  An interesting long list of references on the topic of data analysis.
• Introduction to Deep Neural Networks  [EN]
  Introduction to an interesting topic of Deep Neural Networks with C # code examples.
• Collection of articles and resources on data analysis  [EN]
  A large collection of useful articles and resources on data analysis.
• Another collection of articles and resources on data analysis  [EN]
  Another large collection of useful articles and resources on data analysis.
• Big Data poster  [EN]
  A poster on the topic of Big Data, on which interesting questions about various aspects of working with big data are quite capaciously collected.
• How to Become a Scientist the Data  [to EN]
  Excellent article on how to start their professional career in the field of data analysis.
• Should I do statistics and machine learning?  [EN]
  A very interesting question is being raised that if you want to change your profession to the direction of data analysis, will it be a problem of not very confident knowledge in mathematics. First of all, the discussion of different points of view on this issue in the comments is interesting.
• A series of articles on working with data schemes in MongoDb:
  
  • Data schemes in MongoDb (part 1)  [EN]
    The first part of a series of articles about working with data schemes in MongoDb.
  • Data schemes in MongoDb (part 2)  [EN]
    The second part of a series of articles about working with data schemes in MongoDb.
  • Data schemes in MongoDb (part 3)  [EN]
    The third part of a series of articles about working with data schemes in MongoDb.
• Introduction to Forest the Random  [to EN]
  Simple and easy introduction to machine learning algorithm Random Forest.
• Data Shinobi 2 - Data Shinobi Tree  [EN]
  Continuation of a series of articles on the analysis of large volumes of data, in the second part, the author offers a set of basic problems that a data analysis specialist encounters and the main ways to solve these problems.
• Overview of machine learning algorithms  [EN]
  A brief overview of machine learning algorithms with a description of the key features of the basic algorithms.
• 100+ interesting datasets  [EN]
  More than 100 interesting datasets for data analysis.
• Three interesting articles about overfitting in machine learning:
  
  • The Curse of Dimension  [EN]
    An article explaining the concept of the Curse of Dimensionality in a simple and accessible language.
  • Why retraining is more dangerous than low accuracy of prediction (part 1)  [EN]
    The first part of the discussion of the issue of greater danger of retraining (overfitting) compared with the problem of low accuracy of predicting the result (poor accuracy).
  • Why is retraining more dangerous than low accuracy of prediction (part 2)  [EN]
    The second part of the discussion of the greater danger of retraining (overfitting) compared with the problem of low accuracy of predicting the result (poor accuracy).
• List of useful reading books for data analysis specialist  [EN]
  A good enough short list of books useful for studying (R, Python, Machine Learning).

Videos

• Sentiment classification  [ Sentiment classification ] A
  video on the Sentiment classification on Facebook from a machine learning specialist.
• Hadoop Basics for beginners  [EN]
  Video about the basics of Hadoop family for beginners.
• Natural Language Processing Using the Deep Learning Technique  [EN]
  Description The use of the Deep Learning methodology for Natural Language Processing is a fairly simple and accessible language.