Machine Learning Projects in Python (Paperback)
Language: English
Published by Independently Published, 2026
- Softcover
- New
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
Condition: New
£ 28.46
Quantity: 1 available
Add to basketItem description from seller
Paperback. Ever opened a machine learning book, got buried under equations, and thought, "Cool. but when do I actually build something?" This book is the answer to that question. Machine Learning Projects in Python is a practical, no-fluff, project-driven guide designed for people who want to learn by doing. No endless theory. No academic rabbit holes. Just real-world AI applications built step by step using Python. If you already know basic Python and want to turn it into a real superpower, you're in the right place. What makes this book different? Instead of teaching machine learning as abstract concepts, this book walks you through 10 real-world projects that mirror how ML is actually used in industry. Each chapter focuses on solving a real problem-from predicting house prices to detecting fraud-while quietly teaching you the theory along the way (don't worry, you'll still learn it. just without the boredom). You'll start with setting up your environment and understanding data, then quickly move into building, training, evaluating, and deploying machine learning models. And yes-things will break. That's part of the fun. What you'll build inside this bookA house price prediction systemA spam email detection modelA customer churn prediction engineA movie recommendation systemA fraud detection systemAn image classification applicationA social media sentiment analysis toolA time series forecasting modelPlus deployment-ready machine learning pipelinesEach project is broken into clear, manageable steps so you never feel lost or overwhelmed. What you'll learn (without realizing it)How machine learning really works in practiceData cleaning, preprocessing, and feature engineeringRegression, classification, recommendation systems, NLP, computer vision, and time series forecastingModel evaluation, optimization, and performance tuningHow to turn models into usable, real-world applicationsAll explained in plain English, with humor, encouragement, and the occasional "don't panic, this is normal" moment. Who this book is forPython developers ready to level up into machine learningStudents who want job-ready, project-based skillsDevelopers tired of theory-heavy ML booksAnyone who learns best by building thingsYou don't need a PhD. You don't need to be a math wizard. You just need curiosity and the willingness to try. Final words from the author Machine learning isn't magic. It's a skill-and like any skill, you learn it by doing. This book is your workshop. You'll make mistakes, build cool things, and finish with real projects you can actually show off. If you're ready to stop reading about machine learning and start building with it, let's get started. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…
Seller Inventory # 9798184381824
- Title
- Machine Learning Projects in Python (Paperback)
- Author
- Roman Estavelle
- Publisher
- Independently Published
- Publication year
- 2026
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 13
- 9798184381824
This book is the answer to that question.
Machine Learning Projects in Python is a practical, no-fluff, project-driven guide designed for people who want to learn by doing. No endless theory. No academic rabbit holes. Just real-world AI applications built step by step using Python.
If you already know basic Python and want to turn it into a real superpower, you’re in the right place.
What makes this book different?
Instead of teaching machine learning as abstract concepts, this book walks you through 10 real-world projects that mirror how ML is actually used in industry. Each chapter focuses on solving a real problem—from predicting house prices to detecting fraud—while quietly teaching you the theory along the way (don’t worry, you’ll still learn it… just without the boredom).
You’ll start with setting up your environment and understanding data, then quickly move into building, training, evaluating, and deploying machine learning models.
And yes—things will break. That’s part of the fun.
What you’ll build inside this book
- A house price prediction system
- A spam email detection model
- A customer churn prediction engine
- A movie recommendation system
- A fraud detection system
- An image classification application
- A social media sentiment analysis tool
- A time series forecasting model
- Plus deployment-ready machine learning pipelines
Each project is broken into clear, manageable steps so you never feel lost or overwhelmed.
What you’ll learn (without realizing it)
- How machine learning really works in practice
- Data cleaning, preprocessing, and feature engineering
- Regression, classification, recommendation systems, NLP, computer vision, and time series forecasting
- Model evaluation, optimization, and performance tuning
- How to turn models into usable, real-world applications
All explained in plain English, with humor, encouragement, and the occasional “don’t panic, this is normal” moment.
Who this book is for
- Python developers ready to level up into machine learning
- Students who want job-ready, project-based skills
- Developers tired of theory-heavy ML books
- Anyone who learns best by building things
You don’t need a PhD. You don’t need to be a math wizard. You just need curiosity and the willingness to try.
Final words from the author
Machine learning isn’t magic. It’s a skill—and like any skill, you learn it by doing. This book is your workshop. You’ll make mistakes, build cool things, and finish with real projects you can actually show off.
If you’re ready to stop reading about machine learning and start building with it, let’s get started.
"Synopsis" may belong to another edition of this title.
Grand Eagle Retail
Bensenville, IL, U.S.A.
AbeBooks seller since October 12, 2005
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