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Machine Learning: For Beginners

Definitive Guide for Neural Networks, Algorithms, Random Forests and Decision Trees Made Simple (Machine Learning, Book 1)

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Machine Learning: For Beginners

Auteur(s): Matt Gates
Narrateur(s): Alex Benson
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À propos de cet audio

Have you ever paused and wondered why some companies like Amazon know what you like and make timely recommendations to you?

Have you noticed that some ads are really "sticky" and seem to follow you from your favorite websites to your Facebook or LinkedIn?

Everyone hates spam emails and if you have email accounts from different email providers, you can see which is doing a better job in filtering them out for you.

Machine learning has become an important backend pillar for technologies to innovate and improve while continuing to learn to bring us the best possible results that we desire based on our feedback. With time, the results get better and more accurate which bring us better values such as convenience and save us time.

In this book, you will have a peek into what machine learning is all about and the vast applications which underpin this revolutionary AI technology.

Here's what you will learn:

  • The ins and outs of machine learning algorithms
  • Some of the applications that have been developed as a result of machine learning
  • An important chapter that is fundamental to applying machine learning
  • The building blocks of machine learning
  • Explore the three different types of machine learning algorithms
  • And much more....

Machine Learning: For Beginners: Definitive Guide for Neural Networks, Algorithms, Random Forests and Decision Trees Made Simple is your must-have guide to explore and learn about machine learning, neural networks, algorithms (Markov, Bayes, KNN, and many more), random forests, and decision trees.

PLEASE NOTE: When you purchase this title, the accompanying reference material will be available in your Library section along with the audio.

©2017 Matt Gates (P)2017 Matt Gates
Éducation Apprentissage automatique Science des données Informatique Technologie
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