Constructing Neural Networks with TensorFlow

Have you ever felt like you've grasped deep learning concepts but struggled to build them into real-world applications?

Maybe you've watched countless tutorials without getting your hands dirty. That's not what you signed up for. Without this practical knowledge, you won't make a real impact...

Luckily, this book will teach you the essential skills needed to construct neural networks with TensorFlow in a "hands-on" way.

Unlike other resources, this book emphasizes project-based learning. You will master the fundamentals of TensorFlow and build neural networks for various tasks from scratch.

Using the California Housing Dataset, you'll learn when and how to use different TensorFlow functions for regression and classification tasks!

If you're a beginner, don't worry. A detailed explanation accompanies every code snippet in this book. And if you're already an expert, you might uncover hidden insights you didn't know about.

Here's a sneak peek at the chapters:

• Chapter 1: Welcome!
• Chapter 2: Data Preparation
• Chapter 3: Building Your First Neural Network
• Chapter 4: Evaluating the Regression Model
• Chapter 5: Enhancing the Regression Model
• Chapter 6: Transitioning to Classification
• Chapter 7: Evaluating the Classification Model
• Chapter 8: Finalizing and Deploying Your Model
• Chapter 9: Wrapping Up

Excited? This book is just the beginning. As the field evolves, you'll receive lifetime updates with new chapters and techniques. Imagine it growing to over a hundred pages! Grab it now, and keep learning with me!