include index

Statistics and probability --
Regression --
Time series --
Clustering --
Classification --
Appendix A: Chart types and when to use them.

Embrace machine learning approaches and Python to enable automatic rendering of rich insights. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on minimal time and resources. Python Machine Learning Case Study takes you through the steps to improve business processes and determine the pivotal points that frame strategies. You'll see machine learning techniques that you can use to support your products and services. Moreover you'll learn the pros and cons of each of the machine learning concepts presented. By taking a step-by-step approach to coding in Python you'll be able to understand the rationale behind model selection and decisions within the machine learning process. The book is equipped with practical examples along with code snippets to ensure th at you understand the data science approach to solving real-world problems. You will: Gain insights into machine learning concepts Work on real-world applications of machine learning Get a hands-on overview to Python from a machine learning point of view.