Deep Learning and Neural Networks with Python: A Comprehensive Guide

Author: Ahmed Fawzy Gad

Introduction: “Introduction to Deep Learning and Neural Networks with Python: A Practical Guide” is a step-by-step guide for neuroscientists to fully understand, practice, and build neural networks. This book provides math and Python code examples to clarify neural network calculations, ensuring that by the end, readers will fully understand how neural networks work, starting from the simplest model Y=X and building from scratch.

Key Features:

• Practical Deep Learning: This book examines the practical side of deep learning and neural networks, providing a problem-based approach to building artificial neural networks using real data.
• Python for Neuroscientists: It describes Python functions and features specifically for neuroscientists, helping them understand and implement neural networks in Python.
• Tutorial Approach: The book uses a careful tutorial approach to describe the implementation of neural networks in Python, featuring math and code examples with helpful instructions for easy implementation.

Publication Details:

• Publisher: Elsevier Science
• Publication Date: November 25, 2020
• Language: English
• ISBN: 9780323909334, 9780323909341

Why This Book: This book is essential for neuroscientists looking to understand and apply deep learning and neural networks in their research. With its practical approach and detailed examples, it provides a comprehensive guide to building and understanding neural networks from scratch.