Data Science & Machine Learning for Beginners
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Home > Computing and Information Technology Books > Computer Science Books > Mathematical theory of computation > Data Science & Machine Learning for Beginners: The Step-by-Step Guide to Understanding AI, Analyzing Data, and Building Your First Machine Learning Models - Starting from Zero
Data Science & Machine Learning for Beginners: The Step-by-Step Guide to Understanding AI, Analyzing Data, and Building Your First Machine Learning Models - Starting from Zero

Data Science & Machine Learning for Beginners: The Step-by-Step Guide to Understanding AI, Analyzing Data, and Building Your First Machine Learning Models - Starting from Zero


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About the Book

Are you watching the world run on data and AI - and wondering how to finally understand it for yourself?

Whether you work in healthcare, finance, retail, education, or any other field, data science and machine learning have quietly become the most in-demand skills of the decade. Yet most books on the subject bury beginners under dense mathematics and assume you already know the very things you are trying to learn. This book is different - and it was written precisely for you.

Data Science & Machine Learning for Beginners is the most practical, plain-language guide available for professionals and curious learners who want to build genuine, working skills from absolute zero - no prior programming experience, no advanced mathematics, and no expensive software required.

Written entirely in Python - the world's most in-demand data science language - this book takes you step by step through every stage of the data science journey, from your very first line of code to deploying a real machine learning model that others can use.

Here is exactly what you will gain:

  • A clear, jargon-free understanding of data science, machine learning, and artificial intelligence - what they are, how they work, and why they matter in 2026
  • The practical skills to clean, explore, and visualise real-world datasets using Python, Pandas, Matplotlib, and Seaborn
  • Hands-on experience building and evaluating supervised and unsupervised machine learning models with Scikit-learn
  • A working knowledge of deep learning and neural networks using TensorFlow and Keras - including an image recognition project you build yourself
  • A beginner-friendly introduction to Natural Language Processing and sentiment analysis using real Python code and pre-trained transformer models
  • A complete end-to-end project - from defining a problem to deploying a working web application - that you can add to your professional portfolio
  • An honest, up-to-date picture of AI ethics, real industry applications, and where the field is heading in 2026 and beyond
  • A structured 90-day learning plan to keep your progress moving long after the final chapter

Every chapter includes hands-on exercises using free tools like Google Colab, so you can start practising immediately - no installation required.

This is the book that bridges the gap between "I have heard of machine learning" and "I built something with it." It does not talk down to you, it does not skip the important parts, and it does not leave you stranded when the tutorial ends.

If you are ready to stop watching from the sidelines and start building real skills in the most consequential technology of our time - this is where you begin.

Scroll up and grab your copy today


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Product Details
  • ISBN-13: 9798253195550
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 279 mm
  • No of Pages: 288
  • Returnable: N
  • Sub Title: The Step-by-Step Guide to Understanding AI, Analyzing Data, and Building Your First Machine Learning Models - Starting from Zero
  • Width: 216 mm
  • ISBN-10: 8253195559
  • Publisher Date: 22 Mar 2026
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Spine Width: 15 mm
  • Weight: 720 gr


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