Book Image

The Machine Learning Workshop - Second Edition

By : Hyatt Saleh
Book Image

The Machine Learning Workshop - Second Edition

By: Hyatt Saleh

Overview of this book

Machine learning algorithms are an integral part of almost all modern applications. To make the learning process faster and more accurate, you need a tool flexible and powerful enough to help you build machine learning algorithms quickly and easily. With The Machine Learning Workshop, you'll master the scikit-learn library and become proficient in developing clever machine learning algorithms. The Machine Learning Workshop begins by demonstrating how unsupervised and supervised learning algorithms work by analyzing a real-world dataset of wholesale customers. Once you've got to grips with the basics, you'll develop an artificial neural network using scikit-learn and then improve its performance by fine-tuning hyperparameters. Towards the end of the workshop, you'll study the dataset of a bank's marketing activities and build machine learning models that can list clients who are likely to subscribe to a term deposit. You'll also learn how to compare these models and select the optimal one. By the end of The Machine Learning Workshop, you'll not only have learned the difference between supervised and unsupervised models and their applications in the real world, but you'll also have developed the skills required to get started with programming your very own machine learning algorithms.
Table of Contents (8 chapters)

Program Definition

The following section will cover the key stages required to construct a comprehensive machine learning program that allows easy access to the trained model so that we can perform predictions for all future data. These stages will be applied to the construction of a program that allows a bank to determine the promotional strategy for a financial product in its marketing campaign.

Building a Program – Key Stages

At this point, you should be able to pre-process a dataset, build different models using training data, and compare those models in order to choose the one that best fits the data at hand. These are some of the processes that are handled during the first two stages of building a program, which ultimately allows the creation of the model. Nonetheless, a program should also consider the process of saving the final model, as well as the ability to perform quick predictions without the need for coding.

The processes that we just discussed are...