Overview of the most interesting materials on data analysis and machine learning No. 11 (August 25 - September 1, 2014)

    I present to you the next issue of a review of the most interesting materials on the topic of data analysis and machine learning. This release has a lot of diverse information. There are many articles on the topic of Data Engineering. There are materials for beginners and several video lectures. As Kaggle Machine Learning Competition is commonly referred to. An interesting article about startups in the field of Data Science. A curious article about improving gaming AI using machine learning.

    Data Analysis and Machine Learning Materials

    • EN For newbies Predictive modeling, teacher training and pattern classification A
      good article on machine learning, which will be interesting for beginners as well, which touches on topics such as teaching with a teacher, visualization in machine learning, processing of input data, feature enginering, sampling and others.
    • EN Theory Ruslan Salakhutdinov on Deep Learning at the 2014 KDD Conference
      Materials from a presentation by Ruslan Salakhutdinov from the University of Toronto at the 2014 KDD Conference in New York.
    • RU Habr For newbies Data engineering Talk about Hadoop
      Introduction to the Hadoop ecosystem in Russian. In the end there is a good set of links to useful materials on this topic.
    • EN How to become a Data Scientist An
      interesting article from the DataScienceCentral portal for those interested in the topic of Data Science. The article briefly describes the concept of Data Scientist, identifies 4 areas in this profession and discusses the tools that a data analysis specialist needs.
    • RU R Using the pbapply () function
      An interesting example of using the pbapply () function from the pbapply library for the programming language R.
    • RU Habr Data engineering Azure DocumentDB An
      article about the new NoSQL database from Microsoft called Azure DocumentDB. DomentDB is still in preview. At the end of this article there is a good set of related links.
    • EN Data Science startups from Y Combinator
      In the field of Data Science there are quite a lot of opportunities for business development. This article provides a list of Data Science startups 2014 from the famous startup incubator Y Combinator.
    • RU Machine Learning Competitions New Kaggle Competition: Epilepsy Seizure Prediction Challenge
      Not long ago, a new machine learning competition, the American Epilepsy Society Seizure Prediction Challenge, started at Kaggle. The competition will last until November 17, 2014.
    • EN 33 unusual problems that can be solved using Data Science
      The author of the popular portal DataScienceCentral in his short post published a list of 33 problems from various areas of life that Vincent Granville believes can be solved using Data Science.
    • EN DataScienceCentral Weekly Digest
      Regular weekly data analysis digest from DataScienceCentral.
    • EN Literature List of interesting literature
      A list of interesting books that may be interesting to read for those who are interested in the topic of data analysis.
    • RU A new dataset from Microsoft Research
      Just yesterday, an interesting dataset called Microsoft Research Dense Visual Annotation Corpus was published on the Microsoft Research website.
    • EN How machine learning helped improve game AI
      A rather interesting article written in a good living language about how machine learning techniques helped the author of the article greatly simplify and improve the effectiveness of AI for a game bot.
    • EN Data engineering The convergence of machine learning and Big Data
      The article presents interesting observations by a well-known specialist in data analysis Mikko Braun on the need for convergence of the machine learning communities and Big Data, and that now they are actually quite far from each other, which leads to certain problems and inconveniences.
    • RU For newbies Link Diagrams for Machine Learning and Data Mining
      In this short post, there are two very interesting and useful mind maps on the topics of machine learning and Data Mining.
    • EN Analysis of unstructured data.
      Continuation of a series of articles on text analysis and work with unstructured data. In this case, the author proceeds from posing questions to practical aspects and discusses the topic of processing and cleaning unstructured text data, in preparation for further steps in analyzing this data.
    • EN For newbies So you want to be a Data Scientist
      An interesting short article describing the main aspects of a profession called Data Scientist.
    • EN Using Big Data on the Securities Market
      The author of the article offers 3 practical tips on using Big Data for investment in the securities markets, which everyone can use.
    • EN For newbies Video lectures 100 Popular Machine Learning Videos
      A great, great list of one hundred machine learning videos from VideoLectures.Net.
    • EN For newbies Online course Online Course "Data Analysis and Statistical Inference"
      On Monday, September 1, Coursera launches the second time a very well-proven online course on data analysis and statistics, "Data Analysis and Statistical Inference" from Duke University.
    • EN Digest of the best resources from DataScienceCentral (September 1)
      A good list of fresh interesting articles and resources from DataScienceCentral.
    • EN Data engineering Python Applying Bayesian machine learning methods with Apache Spark
      A little interesting article from the authors of the blog Cloudera, which gives an example of the possibility of using Bayesian machine learning methods with the help of a popular Hadoop family product called Apache Spark and PyMC library for the Python programming language.
    • EN Facts and myths about Big Data
      A small interesting article from the popular portal insideBIGDATA, in which the author discusses the issues of the now popular Big Data topic and shares his thoughts about common misconceptions in this area.
    • EN Data engineering 12 MongoDB Tips
      A short article that contains 12 useful tips for those who want to use the popular NoSQL MongoDB database in combat.
    • EN Video lectures R John Chambers: Interfaces, Performance, and Big Data
      John Chambers in this video from the “useR! 2014 conference ”discusses the past, present and future of the R programming language in a discussion called“ Interfaces, Efficiency and Big Data ”.
    • EN For newbies Data engineering Using Hadoop for large amounts of data
      A fairly large article on the Hadoop ecosystem and its real use when working with large amounts of data.
    • EN Data engineering Write operations in MongoDB
      An article that describes well the subtleties of the issue of writing and updating in MongoDB, citing several modes of working with MongoDB when updating data: Unacknowledged, Acknowledged, Journalled, etc.
    • EN R Nonlinear classification in R using decision trees
      7 types of nonlinear classification using decision trees with code examples in the programming language R from the author of the popular data analysis blog MachineLearningMastery.
    • EN Data engineering Impala: plans for the future
      A small article from the Cloudera blog about the company's plans for the future of the popular Hadoop product called Cloudera Impala, which allows you to work with data in Hadoop using SQL queries.
    • EN Data engineering Slamdata: SQL queries in MongoDB
      Announcement of a rather interesting SlamData product that will allow you to execute SQL queries on data in MongoDB. The product is currently in beta testing, with a release scheduled for early October this year.

    Previous issue:  Overview of the most interesting materials on data analysis and machine learning No. 10 (August 18 - 25, 2014)

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