Machine learningβthe ability of a machine to give right answers based on input dataβhas revolutionised the way we do business. Applied Supervised Learning with Python provides a rich understanding of how you can apply machine learning techniques in your data science projects using Python. You'll explore Jupyter Notebooks, the technology used commonly in academic and commercial circles with in-line code running support.
With the help of fun examples, you'll gain experience working on the Python machine learning toolkitβfrom performing basic data cleaning and processing to working with a range of regression and classification algorithms. Once you've grasped the basics, you'll learn how to build and train your own models using advanced techniques such as decision trees, ensemble modelling, validation, and error metrics. You'll also learn data visualisation techniques using powerful Python libraries such as Matplotlib and Seaborn.
By the end of this book, you'll be equipped to not only work with machine learning algorithms, but also be able to create some of your own!