Python Machine Learning: Practical Guide for Beginners (Data Sciences) by François Duval

Python Machine Learning: Practical Guide for Beginners (Data Sciences)

Book Title: Python Machine Learning: Practical Guide for Beginners (Data Sciences)

Publisher: CreateSpace Publishing

Author: François Duval


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François Duval with Python Machine Learning: Practical Guide for Beginners (Data Sciences)

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Are you thinking of learning more about Machine Learning with Practical Examples using Python?


Machine learning is a field of Artificial Intelligence that uses algorithms to learn from data and make predictions. This means that we can feed data into an algorithm, and use it to make predictions about what might happen in the future.
If you are looking for a book to help you understand how the Machine learning works by using Python, then this is a good book for you.


Several Visual Illustrations and Examples


Instead of tough math formulas, this book contains several graphs and images which detail all algorithms and their applications in all area of the real life.


Why this book is different?


This book takes a different approach that is based on providing simple examples of how machine learning algorithms work, and building on those examples step by step to encompass the more complicated parts of the algorithms.


The book is a practical guide through the basic principles of machine learning, and how to get started with machine learning using Python based on libraries that make it easy to start.


Python Codes for the Examples Shown In the Book


You will build your machine learning and deep learning Model by using Python


There are many languages for building a machine learning model. However, it can also be overwhelming when you start, because there are so many tools to choose. In this book, we choose only Python language.


Target Users


The book designed for a variety of target audiences. The most suitable users would include:
  • Beginners who want to approach machine learning practices, but are too afraid to start

  • Newbies in computer science techniques and machine learning
  • Professionals in data science and social sciences
  • Professors, lecturers or tutors who are looking to find better ways to explain the content to their students in the simplest and easiest way
  • Students and academicians, especially those focusing on machine learning and deep learning


What’s Inside this Book?


  • Introduction to Machine Learning?
  • Essential Libraries and their Installation
  • Basic of Python Language in Machine Learning
  • Data and Inconsistencies in Machine Learning
  • A Roadmap for building Machine Learning Systems
  • Data Cleaning and Preparation
  • Application of Supervised Learning Techniques with Python
  • Applications of unsupervised learning Techniques with python
  • Training Machine Learning Algorithms
  • Combining Different Models for ensemble learning