This class can serve as you complete beginner’s guide to getting your feet wet in the world of machine learning. Machine learning is certainly the future, but it can definitely be intimidating to get started with. However, not to worry! With this starter-level class, we will go over different aspects such as what machine learning actually is, some of the theory behind it, and finally, we will be creating a project in Python to practice our newly acquired knowledge, where we will try some different algorithms in an open source framework.
This book teaches you how to apply the basics of machine learning in Python. You will learn how to build and evaluate predictive models with the help of real-world data, how to perform various types of regression analysis, and how to identify interesting patterns in your data.
Applying the Basics of Machine Learning in Python is a guide to using machine learning in Python, using easy-to-understand examples and clear instructions. The book covers the different types of machine learning, how to train a model, how to test a model, and more. The author provides a number of code examples that demonstrate how to use different machine learning algorithms in Python.
