Machine Learning with Python: A Practical Beginners’ Guide (Learn Machine Learning for Beginners Book 2)

As the second title in the Machine Learning for Beginners series, this book teaches beginners to code basic machine learning models using Python. The book is designed for beginners with basic background knowledge of machine learning, including common algorithms such as logistic regression and decision trees. If this doesn’t describe your experience or if you need a refresher, key concepts from machine learning in the opening chapter and there are overviews of specific algorithms dispersed throughout this book. For a gentle and more detailed explanation of machine learning theory minus the code, I suggest reading the first book in this series Machine Learning for Absolute Beginners (Second Edition), which is written for a more general audience.

In this step-by-step guide you will learn:

- To code practical machine learning prediction models using a range of supervised learning algorithms including logistic regression, gradient boosting, and decision trees
- Clean and inspect your data using free machine learning libraries
- Visualize relationships in your dataset including Heatmaps and Pairplots using just a few lines of simple code
- Develop your expertise in managing data using Python

Please feel welcome to join this introductory course by buying a copy, or sending a free sample to your chosen device.

• Machine Learning For Absolute Beginners: A Plain English Introduction (Second Edition) (Machine Learning From Scratch Book 1)
• Machine Learning: Make Your Own Recommender System (Machine Learning From Scratch Book 3)
• Data Analytics for Absolute Beginners: A Deconstructed Guide to Data Literacy: (Introduction to Data, Data Visualization, Business Intelligence & Machine Learning)
• Statistics for Absolute Beginners: A Plain English Introduction
• Decision Trees and Random Forests: A Visual Introduction For Beginners: A Simple Guide to Machine Learning with Decision Trees
• Machine Learning with Neural Networks: An In-depth Visual Introduction with Python: Make Your Own Neural Network in Python: A Simple Guide on Machine Learning with Neural Networks.
• The Math of Neural Networks
• Data Science from Scratch: First Principles with Python
• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
• Bayesian Statistics the Fun Way: Understanding Statistics and Probability with Star Wars, LEGO, and Rubber Ducks