Ron Kneusel

Practical Deep Learning

A Python-Based Introduction

• Broschiertes Buch

Produktbeschreibung

A book for people with no experience with machine learning and who are looking for an intuition-based, hands-on introduction using Python.

Produktdetails

• Verlag: No Starch Press
• Erscheinungstermin: 23. Februar 2021
• Englisch
• Abmessung: 234mm x 182mm x 32mm
• Gewicht: 882g
• ISBN-13: 9781718500747
• ISBN-10: 1718500742
• Artikelnr.: 60050782

Autorenporträt

Ronald T. Kneusel

Inhaltsangabe

Foreword by Michael C. Mozer, PhD
Acknowledgments
Introduction
Chapter 1: Getting Started
Chapter 2: Using Python
Chapter 3: Using NumPy
Chapter 4: Working With Data
Chapter 5: Building Datasets
Chapter 6: Classical Machine Learning
Chapter 7: Experiments with Classical Models
Chapter 8: Introduction to Neural Networks
Chapter 9: Training A Neural Network
Chapter 10: Experiments with Neural Networks
Chapter 11: Evaluating Models
Chapter 12: Introduction to Convolutional Neural Networks
Chapter 13: Experiments with Keras and MNIST
Chapter 14: Experiments with CIFAR-10
Chapter 15: A Case Study: Classifying Audio Samples
Chapter 16: Going Further
Index

Rezensionen

"Practical Deep Learning with Python is the perfect book for someone looking to break into deep learning. This book achieves an ideal balance between explaining prerequisite introductory material and exploring nuanced subtleties of the methods described. The reader will come away with a solid foundational understanding of the content as well as the practical knowledge required to apply the methods to real-world problems. Deep learning will continue to enable many breakthroughs in artificial intelligence applications and this book covers all that is needed to springboard into this exciting field."
Matt Wilder, longtime neural network practitioner and owner of Wilder AI, a deep learning consulting company

"Kneusel s book tackles machine learning (classification) fantastically, helping anyone with an interest to learn and turning that interest into a skillset for future machine learning projects."
GeekDude, GeekTechStuff