Fundamentals of Machine Learning

Unit No.

CONTENT

1

Unit 1 ⇗:

• Review of Statistical Concepts: Mean, Median, Mode, Outliers, Range, Average Deviation, Absolute Deviation, Squared Deviation, Standard Deviation, Probability theory.
• Review of Linear Algebra:Vectors and Matrices, Matrix operations, Properties, Inverse and Transpose.
• Introduction to Machine Learning: What is Machine Learning, Introduction to ML's three approaches: Supervised, Unsupervised and Reinforcement Learning?

2

Unit 2 ⇗:

• Introduction to Python: • Data types and variables, Operators and operator precedence • Data type conversions, Command line argument, Data input, Comments, Import modules, Control statements.
• Functions and modules in python Python built in functions, Python Modules, File Handling.