Learning Predictive Analytics with Python

"Learning Predictive Analytics with Python" is your hands-on guide to mastering predictive modelling through Python. By working through intuitive explanations and practical examples, you'll understand how to use Python libraries like pandas and scikit-learn to create effective predictive models for various real-world datasets.

What this Book will help me do

• Understand the theory and mathematics underpinning predictive modelling algorithms and implement them programmatically.
• Acquaint yourself with practical data processing techniques, including cleaning and manipulation, using Python's pandas and numpy libraries.
• Gain proficiency in applying predictive analytics methods such as Linear Regression, Logistic Regression, and Clustering.
• Develop skill in writing and modifying Python code for building and testing predictive models from scratch.
• Learn best practices and troubleshooting strategies for deploying predictive analytics solutions on real-world data.

Author(s)

None Kumar and Gary Dougan together bring extensive experience in data science and Python programming. Having published work in machine learning and predictive analytics applications, they blend practical knowledge with theoretical insights. Their approach is to teach complex topics in an accessible and straightforward manner, focusing on hands-on learning.

Who is it for?

"Learning Predictive Analytics with Python" is aimed at data scientists, analysts, and Python programmers eager to delve into predictive analytics. It is ideal for readers with some prior coding experience but beginners in predictive modelling. Aspiring data science professionals and enthusiasts with a solid Python foundation will find this book insightful as they embark on their predictive analytics journey.