Lynda.Introduction.to.Python.Recommendation.Systems.for.Machine.Learning-XQZT

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Appz
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XQZT
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188,10 MB
Files
0
Date
2017-07-18

NFO

Another exquisit release

Lynda.Introduction.to.Python.Recommendation.Systems.for.Machine.Learning-XQZT

     Title: Introduction to Python Recommendation Systems for Machine Learning
 Publisher: Lynda
  Iso Size: 189M (197238784 B)
     Files: 5F
      Date: 07/18/2017

  Course #: 563080
      Type: Big Data
 Published: 7/14/2017
  Modified: N/A
       URL: www.lynda.com/Python-tutorials/Introduction-Python-Recommendation-Systems-Machine-Learning/563080-2.html
    Author: Lillian Pierson, P.E.
  Duration: 1h 38m
     Skill: Intermediate
  Exercise: [X]

Installation:
Unpack that shit, mount that shit, run that shit

Notes:
Discover how to use Python—and some essential machine learning
concepts—to build programs that can make
recommendations. In this hands-on course, Lillian Pierson, P.E.
covers the different types of recommendation systems out there, and
shows how to build each one. She helps you learn the concepts
behind how recommendation systems work by taking you through a
series of examples and exercises. Once you're familiar with the
underlying concepts, Lillian explains how to apply
statistical and machine learning methods to construct your own
recommenders. She demonstrates how to build a
popularity-based recommender using the Pandas library, how to
recommend similar items based on correlation, and how to deploy
various machine learning algorithms to make
recommendations. At the end of the course, she shows how to
evaluate which recommender performed the best.

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