Name: Machine Learning: Study Deep Learning Through Data Science (Step by Step Guide to Machine Learning Techniques for Beginners) (en Inglés)
Price: 92844.00 COP
Availability: InStock
Author: Krauss, Michael
ISBN: 9781777361167

portada Machine Learning: Study Deep Learning Through Data Science (Step by Step Guide to Machine Learning Techniques for Beginners) (en Inglés)

Formato

Libro Físico

Autor

Michael Krauss

Editorial

Michael Krauss

Idioma

Inglés

N° páginas

192

Encuadernación

Tapa Blanda

Dimensiones

20.3 x 12.7 x 1.0 cm

Peso

0.20 kg.

ISBN13

9781777361167

Categorías

Teoría matemática de la computación
Machine learning: aprendizaje automático
Reconocimiento de formas
Visión por ordenador
Autoayuda y desarrollo personal

Machine Learning: Study Deep Learning Through Data Science (Step by Step Guide to Machine Learning Techniques for Beginners) (en Inglés)

Michael Krauss (Autor) · Michael Krauss · Tapa Blanda

Libro Físico

$ 92.844

$ 154.740

Ahorras: $ 61.896

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Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

Se enviará desde nuestra bodega entre el Miércoles 05 de Junio y el Miércoles 19 de Junio.

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Reseña del libro "Machine Learning: Study Deep Learning Through Data Science (Step by Step Guide to Machine Learning Techniques for Beginners) (en Inglés)"

This book is for anyone who would like to learn how to develop machine-learning systems. We will cover the most important concepts about machine learning algorithms, in both a theoretical and a practical way, and we'll implement many machine-learning algorithms using the scikit-learn library in the python programming language. In the first chapter, you'll learn the most important concepts of machine learning, and, in the next chapter, you'll work mainly with the classification. In the last chapter you'll learn how to train your model. I assume that you've knowledge of the basics of programming. What you'll learn: What is machine learningWhat is supervised, unsupervised, and reinforcement learningHow to use the numpy and pandas libraryHow to use matplotlib to plot chartsWhat is the scikit-learn library?What do the fit() and transform() methods doHow to pre-process our dataHow to use pipelines and column transformers to streamline our codeHow to evaluate our modelsMachine learning is the way of the future - and breaking into this highly lucrative and ever-evolving field is a great way for your career, or business, to prosper. Inside this guide, you'll find simple, easy-to-follow explanations of the fundamental concepts behind machine learning, from the mathematical and statistical concepts to the programming behind them.