Machine learning with python: A Beginner's guide to data science and real-world projects

Book Description: What if you could go from machine learning novice to building production-ready models-without drowning in math or theory?Machine Learning with Python: From Fundamentals to Real-World Projects is your complete beginner's guide to mastering the core concepts of machine learning-while actually building something that matters.This book strips away the jargon and walks you step-by-step through the real-world process of designing, training, and deploying machine learning models using Python. From understanding algorithms like linear regression and decision trees to building intelligent web apps, you'll not only learn ML-you'll do it.Whether you're a curious beginner, a data enthusiast, or a developer transitioning into AI, you'll gain hands-on experience with tools like Scikit-learn, Pandas, Matplotlib, Flask, Streamlit, and more. Along the way, you'll tackle practical projects like predicting house prices, classifying spam emails, and deploying real-time web applications-boosting your portfolio and confidence.Key benefits you'll gain from this book: Learn the essentials of ML through clear explanations and working Python examplesGet your hands dirty with real projects from day one-no fluff, no fillerMaster data preprocessing, model evaluation, feature engineering, and deploymentUnderstand advanced topics like hyperparameter tuning, unsupervised learning, MLOps, and AutoMLBuild a job-ready portfolio with guided, industry-relevant mini-projectsWhat makes this book different? It's built for action-oriented learners who want more than theory. You won't just read about ML-you'll build, debug, test, deploy, and improve real solutions with real data.Ready to future-proof your skills and break into one of the most exciting fields in tech?Grab your copy of Machine Learning with Python today and start creating intelligent systems that solve real problems-one line of code at a time.

Author:

Kelvin Lowe

Publisher:

Independently Published

Publication Date:

Jul 12, 2025

Number of pages:

218 pages

Binding:

Paperback or Softback

ISBN-13:

9798292251767