Chapters authored
Fundamental Concepts and Algorithms in Machine Learning
This chapter will enable readers to glance through the Machine learning landscape topology. It covers the fundamental Concept of machine learning, Algorithms in Machine Learning, usefulness of machine learning and other tips that will empower readers to get the best out of machine learning and its related Field. This chapter consists of 25 sections. Sections 1–10, covers but not limited to: Introduction to machine learning, Prerequisite to Machine Learning, Machine learning Algorithm, its categories, and the application of machine learning. While sections 11–20 topics includes, Perceptron, artificial neural network (ANN), model evaluation, principal component Analysis, and model parameter. Sections 21–25 cover such topics as: Errors in machine learning, bias, life cycle of machine learning, data gathering methodology, data set, population based algorithm, and conclusion. This chapter, also, discussed future of machine learning, and other key term required to the understanding of machine learning as a topic. The chapter showcase machine learning in such a way that new theory, knowledge, understanding, in the area of interest would emerge from reading it, as a topic, and in the area of application.
Part of the book: Advanced Virtual Assistants - A Window to the Virtual Future