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)

Introducing Neural Nets for Predictive Analytics

In the last two chapters, we have presented some of the most basic and popular models for regression and classification tasks. In this chapter, we introduce a family of models based on neural networks. This family of models is the basis for the field of deep learning—an approach to machine learning behind some of the most exciting and recent advances in the field of artificial intelligence.

This chapter will give you enough knowledge to be able to use neural networks for predictive analytics; the point here is to present the fundamental concepts about these models and learn to train the most fundamental type of neural network—the multilayer perceptron (MLP).

First, we will cover the main concepts of neural networks when talking about the anatomy of an MLP; then we will discuss how these models learn to make predictions...