Publisher's Synopsis
Build Smarter Software with Machine Learning-Without Starting from Zero
If you're a programmer who wants to break into artificial intelligence, Machine Learning for Programmers is your fast track. This book skips the math-heavy theory and goes straight into building intelligent, real-world applications using Python.
Designed for developers, not data scientists, this guide focuses on practical implementation: loading data, training models, testing predictions, and deploying ML systems using tools you already know-like Python, scikit-learn, and TensorFlow.
What You'll Learn:Core ML concepts made simple for coders
How to build classification, regression, and clustering models
Real-world projects: spam filters, recommendation engines, and more
Step-by-step tutorials using Python and popular ML libraries
Data preparation and feature engineering explained clearly
Hyperparameter tuning, model evaluation, and cross-validation
The basics of neural networks and deep learning
How to deploy models into live applications and services
Best practices for clean, testable, production-ready ML code
You don't need a PhD to get started-just Python skills and a problem to solve.
Code smarter. Think in models. Build the future.
