MACHINE LEARNING: Beginner to Intermediate’s Guide in Python/r/Scala

Machine Learning: Beginner to Intermediate’s Guide in Python/R/Scala


Are you thinking of learning more about Machine Learning?


Want to learn Machine Learning Algoirthms?


Do you want to explore Python/R/Scala libraries for Machine Learning?


Then You are at right place


A Bundle of Two Awesome Books for Machine Learning Lovers


This bundle and the accompanying examples, you would be well suited to tackle problems which enhance your interests using machine learning. The title opens with a general introduction to machine learning from a macro level. The second half of the book is more practical and dives into introducing mathematical concepts, specific algorithms, introduction to programming languages, best programming languages for Machine Learning and libraries of Python applied in Machine Learning.


It would seek to explain common terms and algorithms in an intuitive way. The authors used a progressive approach whereby we start out slowly and improve on the complexity of our solutions.

This bundle and the accompanying examples, you would be well suited to tackle problems which enhance your interests using machine learning. The title opens with a general introduction to machine learning from a macro level. The second half of the book is more practical and dives into Data Processing, Regression, Classification, Clustering, Natural Language Processing and Deep Learning.


Just a few more benefits this bundle will provide:



  • Introduction to Programming Language

  • Tools for Machine Learning

  • Introduction to MLlib (Apache Spark)

  • Libraries of Python

  • Master Machine Learning on Python & R.

  • Have a Great intuition of many Machine Learning models

  • Regression & Classification

  • Handle specific topics like NLP, Clustering & Deep Learning






Download your copy now so you can get started on what is promising to be a most amazing future.




Copyright:© 2018 by Thomas Farth, All rights reserved.




















Book details

  • Authors:Thomas Farth
  • Pages:133 pages
  • Format:azw3
  • Size:0.33Mb
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