ABSTRACT
From this chapter onwards, we will describe the application of Python programming language in various Machine Learning algorithms. Therefore, this chapter will introduce the readers to the exciting field of Machine Learning and its wide range of applications in the modern-day era, as well as its applications in the field of life sciences. Next, we will cover the terminologies in Machine Learning, the types of Machine Learning (i.e. supervised, unsupervised, semi-supervised, and reinforcement learning), testing, validation, and evaluation of models, optimization of parameters, and challenges in Machine Learning tasks. The second section of the chapter elaborates on one of the supervised Machine Learning algorithms used for the prediction of continuous variables - linear regression. The chapter then covers the step-by-step usage of Python in the biological applications of linear regression, beginning from loading the dataset until its implementation in Scikit-Learn. The Jupyter Notebook template for the implementation of a linear regressor is also provided with the supplementary files.
