Countdown header img desk

MAI SUNT 00:00:00:00

MAI SUNT

X

Countdown header img  mob

MAI SUNT 00:00:00:00

MAI SUNT

X

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

De (autor): Vahid Mirjalili , Sebastian Raschka

0
(0 review-uri)
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

De (autor): Vahid Mirjalili , Sebastian Raschka

0
(0 review-uri)
 Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning.
 
Key Features:
- Third edition of the bestselling, widely acclaimed Python machine learning book
- Clear and intuitive explanations take you deep into the theory and practice of Python machine learning
- Fully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practices
 
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.
 
Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.
 
Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.
 
This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.
 
What you will learn:
Master the frameworks, models, and techniques that enable machines to 'learn' from data
Use scikit-learn for machine learning and TensorFlow for deep learning
Apply machine learning to image classification, sentiment analysis, intelligent web applications, and more
Build and train neural networks, GANs, and other models
Discover best practices for evaluating and tuning models
Predict continuous target outcomes using regression analysis
Dig deeper into textual and social media data using sentiment analysis
 
If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.
Citeste mai mult

24-48h

-25%

transport gratuit

PRP: 199.95 Lei

!

Acesta este Pretul Recomandat de Producator. Pretul de vanzare al produsului este afisat mai jos.

149.96Lei

149.96Lei

199.95 Lei

Primesti 149 puncte

Important icon msg

Primesti puncte de fidelitate dupa fiecare comanda! 100 puncte de fidelitate reprezinta 1 leu. Foloseste-le la viitoarele achizitii!

Indisponibil

Plaseaza rapid comanda

Important icon msg

Completeaza mai jos numarul tau de telefon

Poti comanda acest produs introducand numarul tau de telefon. Vei fi apelat de un operator Libris.ro in cele mai scurt timp pentru prealuarea datelor necesare.

Descrierea produsului

 Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning.
 
Key Features:
- Third edition of the bestselling, widely acclaimed Python machine learning book
- Clear and intuitive explanations take you deep into the theory and practice of Python machine learning
- Fully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practices
 
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.
 
Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.
 
Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.
 
This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.
 
What you will learn:
Master the frameworks, models, and techniques that enable machines to 'learn' from data
Use scikit-learn for machine learning and TensorFlow for deep learning
Apply machine learning to image classification, sentiment analysis, intelligent web applications, and more
Build and train neural networks, GANs, and other models
Discover best practices for evaluating and tuning models
Predict continuous target outcomes using regression analysis
Dig deeper into textual and social media data using sentiment analysis
 
If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.
Citeste mai mult

Detaliile produsului

De pe acelasi raft

Parerea ta e inspiratie pentru comunitatea Libris!

Acum se comanda

Noi suntem despre carti, si la fel este si

Newsletter-ul nostru.

Aboneaza-te la vestile literare si primesti un cupon de -10% pentru viitoarea ta comanda!

*Reducerea aplicata prin cupon nu se cumuleaza, ci se aplica reducerea cea mai mare.

Ma abonez image one
Ma abonez image one