Mastering Machine Learning: A Practical Guide with Scikit-Learn, TensorFlow & Keras - Softcover

Edward, Lucas

Softcover

ISBN 13: 9798293982127

Publisher: Independently published, 2025

Synopsis

Master Machine Learning. Build Real Projects. Transform Your Future.

Are you ready to stop reading and start building?

Mastering Machine Learning: A Practical Guide with Scikit-Learn, TensorFlow & Keras is not just another machine learning book — it’s your roadmap to real, applicable skills in one of the world’s most in-demand fields.

From foundational algorithms to advanced deep learning models, this guide walks you step-by-step through the entire ML lifecycle, using three of the most powerful libraries in modern AI development.

If you’re a developer, data analyst, student, or career-changer looking to build smart, scalable systems that actually work — this is the book that will get you there.

🔧 What You'll Master:

• Scikit-Learn Essentials: Train and tune classic ML models with ease
• Deep Learning with TensorFlow & Keras: Build and deploy neural networks, CNNs, and more
• Real-World Use Cases: Tackle projects like fraud detection, sentiment analysis, image recognition, and time series forecasting
• Hands-On Code: Every chapter includes clean, documented Python code you can run and customize
• Best Practices & Pitfalls: Learn what works — and what to avoid — from real industry workflows

🚀 Why This Book Works:

• Practical from Page One: No endless theory. Just the tools and examples you need to start building now
• Zero to Hero Learning Path: Start with the basics. Finish with confidence
• Built for Results: Whether you're aiming for a new job, launching a startup, or leveling up your career, this book delivers

AI is changing the world — and those who understand it will shape the future. This is your chance to join them.

Don’t wait to be left behind.
Click “Buy Now” and begin your journey to machine learning mastery — today.

Edition details

• Publisher: Independently published
• Publication date: 2025
• Language: English
• ISBN 13: 9798293982127
• Binding: Paperback
• Number of pages: 117