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)

Artificial Neural Networks

Although there are several machine learning algorithms available to solve data problems, as we have already stated, ANNs have become increasingly popular among data scientists, on account of their ability to find patterns in large and complex datasets that cannot be interpreted by humans.

The neural part of the name refers to the resemblance of the architecture of the model to the anatomy of the human brain. This part is meant to replicate a human being's ability to learn from historical data by transferring bits of data from neuron to neuron until an outcome is reached.

In the following diagram, a human neuron is displayed, where A represents the dendrites that receive input information from other neurons, B refers to the nucleus of the neuron that processes the information, and C represents the axon that oversees the process of passing the processed information to the next neuron:

Figure 5.1: Visual representation of a human...