Book Image

Mastering Predictive Analytics with scikit-learn and TensorFlow

By : Alvaro Fuentes
Book Image

Mastering Predictive Analytics with scikit-learn and TensorFlow

By: Alvaro Fuentes

Overview of this book

Python is a programming language that provides a wide range of features that can be used in the field of data science. Mastering Predictive Analytics with scikit-learn and TensorFlow covers various implementations of ensemble methods, how they are used with real-world datasets, and how they improve prediction accuracy in classification and regression problems. This book starts with ensemble methods and their features. You will see that scikit-learn provides tools for choosing hyperparameters for models. As you make your way through the book, you will cover the nitty-gritty of predictive analytics and explore its features and characteristics. You will also be introduced to artificial neural networks and TensorFlow, and how it is used to create neural networks. In the final chapter, you will explore factors such as computational power, along with improvement methods and software enhancements for efficient predictive analytics. By the end of this book, you will be well-versed in using deep neural networks to solve common problems in big data analysis.
Table of Contents (7 chapters)

Introduction to ANNs

ANNs are biologically inspired computational models that can be used to train a computer to perform a task using data. These models are part of the broad category of machine learning models. The distinction between these models and others is that these models are based on a collection of connected units called artificial neurons.

There are many types of ANNs and, in this book, we will use one specific type, which is called the multilayer perceptron (MLP). Please note that there are a lot more variations of ANNs. These are machine learning models and we can use them for classification and regression tasks, but we can actually extend these models and apply them to other very specific tasks such as computer vision, speech recognition, and machine translation. These models are the basis of the exciting and growing field of deep learning, which has been really...