Machine Learning with Python: A Practical Beginners' Guide (Machine Learning From Scratch Book 2) / Oliver Theobald

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.

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