Machine Learning: Fundamental Algorithms for Supervised and Unsupervised Learning With Real-World Applications (Advanced Data Analytics)

Chapmann, Joshua

ISBN 10: 1548307750 / ISBN 13: 9781548307752

Edité par CreateSpace Independent Publishi, 2017

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Détails bibliographiques

Titre : Machine Learning: Fundamental Algorithms for...

Éditeur : CreateSpace Independent Publishi

Date d'édition : 2017

Reliure : Paperback

Etat : Good

A propos de ce titre

Synopsis :

machine learning

Présentation de l'éditeur:

Computers can't LEARN... Right?!

Machine Learning is a branch of computer science that wants to stop programming computers using a list of detailed instructions and instead use a set of high-level commands which they can apply to many unknown scenarios – these are called algorithms.

In practice, they want to give computers the ability to Learn and to ADAPT.

We can use these algorithms to obtain insights, recognize patterns and make predictions from data, images, sounds or videos we have never seen before (or even knew existed). Unfortunately, the true power and applications of today’s Machine Learning Algorithms is misunderstood by most people.

Through this book I want fix this confusion, I want to shed light on the most relevant Machine Learning Algorithms used in the industry:

Supervised Learning Algorithms

• K-Nearest Neighbour

• Naïve Bayes

• Regressions

Unsupervised Learning Algorithms:

• Support Vector Machines

• Decision Trees