Abstract
Machine Learning is referred to as the subset of Artificial Intelligence. It
involves a machine being learned without programming it explicitly. In Machine
Learning, machines try to improve their performance with the help of past experiences
or by using training examples. The following chapter discusses Machine Learning,
Selection of training set, Selection of target function, Selection of Function
Approximation Algorithm, Perspectives and issues involved while building a machine
learning system,In-sample and Out-of-sample error and Applications of Machine
Learning.
Keywords: Data science, Jupyter, Machine learning, Matplotlib, Numpy, Python, Scikit learn, SciPy.
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