Book Image

Hands-On Predictive Analytics with Python

By : Alvaro Fuentes
Book Image

Hands-On Predictive Analytics with Python

By: Alvaro Fuentes

Overview of this book

Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming.
Table of Contents (11 chapters)

The Predictive Analytics Process

This will be the only conceptual chapter of the book; you may want to start coding and building predictive models from the start, but trust me, we need a common understanding of the fundamental concepts that we will use in the rest of the book. First, we will discuss in detail what predictive analytics is, then we will define some of the most important concepts of this exciting field. With those concepts as a foundation, we will go on to provide a quick overview of the stages in the predictive analytics process, and finally briefly talk about them, as we will devote entire chapters to each of them in the rest of the book.

The following topics will be covered in this chapter:

  • What is predictive analytics?
  • A review of important concepts of predictive analytics
  • The predictive analytics process
  • A quick tour of Python's data science stack