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  • Feature Selection For Unsupervised Learning
    This is my presentation for the IBM data science day, July 24. Abstract After reviewing popular techniques used in supervised, unsupervised and semi-supervised machine learning, we focus on feature selection methods in these different contexts, especially the metrics used to assess the value of a feature or set of features, be it binary, continuous or […]
    Vincent Granville
  • Practical Apache Spark in 10 minutes. Part 2 - RDD
    Spark’s primary abstraction is a distributed collection of items called a Resilient Distributed Dataset (RDD). It is a fault-tolerant collection of elements which allows parallel operations upon itself. RDDs can be created from Hadoop InputFormats (such as HDFS…
    Igor Bobriakov
  • Machine Learning with C++ - Classification with Shogun library
    Hello, with this article I'm starting series of articles about full featured C++ Machine Learning frameworks . This articles covers how to use Shogun library for solving classification problem. Shogun is an open-source machine learning library that offers a wide range of machine learning algorithms. From my point of view it's not very popular among […]
    Kyrylo Kolodiazhnyi
  • Comparing AI Strategies – Vertical vs. Horizontal
    Summary:  Getting an AI startup to scale for an IPO is currently elusive.  Several different strategies are being discussed around the industry and here we talk about the horizontal strategy and the increasingly favored vertical strategy.   Looks like there’s a…
    William Vorhies
  • A Basic Introduction to Reading and Writing CSV Files using Pandas
    Pandas dataframe is making life a lot easier if you are working with data. A lot of data comes in CSV format. It's possible to read CSV files to a Pandas dataframe. In fact, it's quite easy using read_csv. In the video below we will learn the basics of just loading a CSV file to a […]
    Erik Marsja

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