Overview
'Python Deep Learning' thoroughly guides you through the realm of neural networks and deep learning techniques. From fundamental principles to cutting-edge innovations like large language models, this book includes real-world examples to ensure you can apply what you learn effectively.
What this Book will help me do
- Understand the mathematical foundations of deep learning.
- Design and train convolutional neural networks for computer vision tasks.
- Master the attention mechanism and transformers for text-related problems.
- Implement algorithms using popular frameworks like PyTorch and Keras.
- Apply MLOps principles to deploy robust deep learning models.
Author(s)
Ivan Vasilev is an experienced software engineer and researcher specializing in deep learning and artificial intelligence. With years of expertise in hands-on neural network implementations, Ivan combines fundamental theory with practical applications to guide readers effectively through the topics. He is committed to providing clear explanations to make complex subjects accessible.
Who is it for?
This book is perfect for software developers, data scientists, and students eager to delve into deep learning, provided they have a working knowledge of Python. Readers should be keen to understand neural networks and their applications in fields like computer vision and natural language processing. They should also be motivated to learn about contemporary innovations like transformers and MLOps.