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Master Machine Learning & Python: A Beginner’s Guide to ML Algorithms, Python Programming Basics, Supervised Learning, AI Essentials, Hands-On Coding & Real-World Applications (Set of 2 Books)
Estimated delivery between August 28 and August 30.
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Master Machine Learning & Python: A Beginner’s Guide to ML Algorithms, Python Programming Basics, Supervised Learning, AI Essentials, Hands-On Coding & Real-World Applications (Set of 2 Books)
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Description
Python is the foundation of machine learning—and this combo helps you master both in the right sequence:
- Start mastering Python programming step by step
- Move on to applying your skills to real ML problems
- Learn concepts through practical examples and simplified theory
- Transition smoothly from beginner to confident ML coder
What each book offers?
Book 1: Machine Learning Essentials You Always Wanted to Know
With this book, you will:
- Learn how data fuels modern machine learning systems, from training algorithms to making accurate predictions
- Understand the core concepts of supervised and unsupervised learning, including key techniques like regression and classification
- Tackle complex topics like deep learning and neural networks—made easy with clear, beginner-friendly explanations
- Discover how ML is applied in the real world, with examples from industries like healthcare, education, and more
Click here to learn more about the book
Book 2: Python Essentials You Always Wanted to Know
With this book, you will:
- Gain a solid foundation in Python, making it easier to progress to more advanced topics with simple and step-by-step explanations
- Get a deep understanding of object-oriented programming principles, which are vital skills for writing clean, scalable, and reusable Python code
- Learn how to handle errors and exceptions, making sure your code runs smoothly and efficiently
- Stay ahead of the curve by diving into exciting fields like AI, Machine Learning, and IoT with Python
Bibliographic Details
Pages: 574 pages
Paperback (ISBN): 9781636516035
Category: Business & Economics
Author: Dhairya Parikh, Shawn Peters, Vibrant Publishers
Table of Contents
Click on individual book titles below to view their complete Table of Contents.
Author
Dhairya Parikh is a seasoned data engineer, a graduate of the University of Waterloo, and a technical writer with expertise in AI, data science, and practical ML applications.
Shawn Peters has 19 years of teaching experience, is certified in Python Programming Teaching from the College of the North Atlantic, and also specializes in JavaScript and Java.
Vibrant Publishers is focused on presenting the best texts for learning about technology and business as well as books for test preparation. Categories include programming, operating systems and other texts focused on IT. In addition, a series of books helps professionals in their own disciplines learn the business skills needed in their professional growth.
Vibrant Publishers has a standardized test preparation series covering the GMAT, GRE and SAT, providing ample study and practice material in a simple and well organized format, helping students get closer to their dream universities.
Series
The Self-Learning Management Series is designed to help students, new managers, career switchers, and entrepreneurs learn essential management lessons and covers every aspect of business, from HR to Finance to Marketing to Operations across any and every industry. Each book includes basic fundamentals, important concepts, and standard and well-known principles as well as practical ways of application of the subject matter.
Editorial Reviews
What a great introduction to this topic, especially for a non-programmer like myself! The examples provided are easy to understand and apply, allowing me to try it out for myself to further cement my understanding of the steps involved. Read, See, Do. A great way to learn. I really enjoyed the quizzes at the end of each chapter, as they emphasized what the important takeaways were and reinforced what I did know - and what I didn’t. I’ll probably never become a programmer, but understanding how programming works is an asset to any user.
-- Sharon Peach B.Sc, B.Ed, M.Ed
This beginner-friendly guide makes mastering this versatile language accessible for everyone. It provides clear explanations and practical examples while avoiding technical jargon, making it perfect for absolute beginners and those at various skill levels. Even as someone who isn’t usually into programming, I found it easy to follow!
-- Samantha Nichols
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- 5 stars: 51 (84%)
- 4 stars: 10 (16%)
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Comprehensive books that cover every single core pillar of modern data science.
Straight to the point guidelines on writing efficient, clean Python code.
Great variety of practice exercises covering supervised and unsupervised learning.
Helped me overcome my hurdles with neural network architectures.
Completely transformed how I architect data pipelines and model evaluation scripts.
Using this bundle kept me focused and disciplined during my weekend coding sessions.
The best investment any software developer can make into learning AI fundamentals.
Great coverage of data wrangling, NumPy arrays, and vectorized operations.
The depth of coverage on deep learning libraries is remarkable for a bundle.
Complex object-oriented programming concepts are broken down into digestible parts.
This bundle was instrumental in helping me secure my first machine learning role.
Solid formatting and comprehensive explanations of regression and classification trees.
No fluff, just solid machine learning principles and clean Python code snippets.
The data preprocessing chapters gave me a framework I now use daily.
The end-of-chapter projects ensure you actually retain what you read.
Everything you need to master Python for machine learning is packed into this bundle.
My understanding of scikit-learn and data visualization improved immensely.
Challenging practice projects that test your ability to build production-ready models.
Clean layout and robust code repositories referenced throughout the book.
A complete roadmap for anyone wanting to pivot into machine learning engineering.
The mathematical logic behind algorithms is explained in an approachable, developer-friendly way.
Comprehensive coverage of data structures, libraries, and machine learning principles.
The hands-on exercises provided in the bundle are fantastic for real-world application.
An incredible collection that demystifies artificial intelligence for intermediate coders.
If you want a thorough grounding in Python and machine learning, this is the book to get.
Helped me upskill quickly for AI integration projects at my firm in Bangkok.
The progression from data cleaning to predictive modeling is logical and smooth.
Very structured approach to learning algorithms, data processing, and neural network fundamentals.
This bundle bridges the gap between basic Python scripting and advanced machine learning models seamlessly.
The practical examples using pandas and scikit-learn are extremely clear and easy to follow.
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Vibrant Publishers India.