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

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

Articles

• References for the summer [EN]
  An interesting long list of references devoted to the topic of data analysis.
• Introduction to Deep Neural Networks [EN]
  An introduction to the interesting topic of Deep Neural Networks with examples of C # code.
• Collection of articles and resources for data analysis [EN]
  A large collection of useful articles and resources devoted to data analysis.
• Another collection of articles and resources on data analysis [EN]
  Another large collection of useful articles and resources devoted to data analysis.
• Big Data Poster [EN]
  A poster on the topic of Big Data, which is quite capaciously collected interesting questions about various aspects of working with big data.
• How to become a Data Scientist [EN]
  Excellent article about how to start your professional journey in the field of data analysis.
• Is it worth doing statistics and machine learning? [En]
  A very interesting question is raised that if you want to change the profession to the direction of data analysis, then the problem is not very confident knowledge in mathematics. First of all, it is interesting to discuss different points of view on this question in the comments.
• A series of articles on working with data schemas in MongoDb:
  
  • Data Schemes in MongoDb (Part 1) [EN]
    The first part of a series of articles about working with data schemas in MongoDb.
  • Data Schemes in MongoDb (Part 2) [EN]
    The second part of a series of articles about working with data schemas in MongoDb.
  • Data Schemes in MongoDb (Part 3) [EN]
    The third part of a series of articles about working with data schemas in MongoDb.
• Introduction to Random Forest [EN]
  A simple introduction to the Random Forest machine learning algorithm.
• Data Shinobi 2 - Data Shinobi Tree [EN]
  Continuation of a series of articles on the analysis of large amounts of data, in the second part the author offers a set of basic problems faced by a data analyst and the main ways of solving these issues.
• Machine Learning Algorithm Overview [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 curious datasets for data analysis.
• Three interesting articles about retraining (overfitting) in machine learning:
  
  • About the curse of dimension [EN]
    An article explaining the notion of curse of dimension (Curse of Dimensionality) in simple and accessible language.
  • Why retraining is more dangerous than low prediction accuracy (part 1) [EN]
    The first part of the discussion of the greater danger of retraining (overfitting) compared to the problem of poor accuracy of prediction of the result (poor accuracy).
  • Why retraining is more dangerous than low prediction accuracy (part 2) [EN]
    The second part of the discussion of the issue of greater danger of retraining (overfitting) compared with the problem of low accuracy of prediction of results (poor accuracy).
• A list of useful books for a data analyst [EN]
  A good enough short list of useful books for learning (R, Python, Machine Learning).

Video

• Sentiment classification of text ( EN)
  Video about text tonality classification (Sentiment classification) on Facebook from a machine learning specialist.
• Hadoop basics for newbies [EN]
  Video about the basics of the Hadoop family for beginners.
• Natural Language Processing with Deep Learning [EN]
  Description of the application of the Deep Learning method for natural language processing (Natural Language Processing) in a fairly simple and accessible language.