Title: Data Science from Scratch to Production: A Complete Guide to Python, Machine Learning, Deep Learning, Deployment & MLOps (The Complete Data Science & AI Engineering Series)
Publisher: Independently published
Publication Date: 2026
Language: English
ISBN 13: 9798254141723
Binding: Soft cover
Condition: New

About this title

Synopsis

Become a Job-Ready Data Scientist with Real-World, Production-Level Skills

Most data science books focus on theory. They explain algorithms, define concepts, and stop before showing how real systems are built and deployed.

This book takes a different approach.

It is designed to guide you step by step from the fundamentals of data science to building and deploying production-ready machine learning systems used in real-world applications.

What You Will Learn

This book provides a complete roadmap covering every stage of the data science lifecycle:

Python programming for data science
Data analysis using NumPy and Pandas
Data cleaning and preprocessing techniques
Exploratory Data Analysis and visualization
Machine learning fundamentals and algorithms
Regression and classification models
Decision trees, random forest, and clustering
Model evaluation and performance optimization
Feature engineering and data transformation
Deep learning and neural networks
End-to-end machine learning project implementation
Model deployment using APIs and Docker
MLOps concepts, pipelines, monitoring, and retraining

Practical, Real-World Approach

This is not just a theoretical guide. You will learn how to:

Work with real datasets
Build complete machine learning pipelines
Evaluate and improve model performance
Deploy models into production environments
Understand how scalable AI systems are designed

Every section is structured to help you move from understanding concepts to applying them in real scenarios.

Who This Book Is For

Beginners starting their data science journey
Software developers transitioning into machine learning and AI
Professionals looking to build production-level skills
Anyone who wants to understand how real-world data science systems work

No prior experience in machine learning is required. The book starts from the basics and gradually moves to advanced topics.

Why This Book Is Different

Unlike most books that stop at model building, this guide covers the full lifecycle of data science:

From raw data to trained models
From models to deployed APIs
From deployment to monitoring and MLOps

This makes it a complete and practical resource for modern data science and AI engineering.

What You Will Achieve

By the end of this book, you will be able to:

Build machine learning models from scratch
Work with real-world datasets and solve practical problems
Deploy models using APIs and containerization tools
Understand and implement production-level ML systems
Create projects that strengthen your portfolio and career opportunities

Part of a Complete Learning Series

This book is part of the Complete Data Science and AI Engineering Series, designed to take you from beginner to advanced levels through structured, practical learning.

"About this title" may belong to another edition of this title.

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