Teaching Learning Centre Indian Institute of Technology Hyderabad (Under PMMMNMTT, MHRD)

Teaching Repository

Artificial Intelligence and Machine Learning

Material used in IIT Hyderabad Artificial Intelligence and Machine Learning department courses

EE1510: Matrix Analysis

1:Matrix Analysis through Python


The manual introduces a system of equations with no solution, which is solved using Moore-Penrose pseudo inverse in Python. An alternative method for obtaining the pseudo inverse using SVD is also employed. In the process, all basic concepts in matrix analysis like eigenvalues, eigenvectors, orthogonality, Gram-Schmidt orthogonalization, symmetric matrices and SVD are covered.

EE1520: Data Analytics

1:Random Variables in Python.


This manual provides a simple introduction to elementary probability and random variables. This is done by generating random variables in Python and computing metrics like the CDF and PDF for some random variables. In the process, basic concepts like hypothesis testing, transformation of random variables, central limit theorem, etc.. are introduced.

2:Linear Classification.


This manual provides an introduction to linear methods in regression.

EE2250: Optimization

1:Covex Optimization in Python.


This manual provides a simple introduction to convex optimization through graphical and numerical computation using python libraries. The Karuch-Kuhn-Tucker (KKT) conditions are explained through examples. Linear Programming (LP) and Semi Defininte Programming (SDP) problems are also introduced and shown to be convex optimization problems through examples. Further, the freely available CVXOPT python library is used for solving LP and SDP problems.

2:Simplex Method.


This manual explains the Simplex Method for solving Linear Programming problems through examples.

3:Transportation Problem.


This manual explains the Northwest corner cell method, Modi Method, and using cvxopt for solving Transportation problems through examples.

4:GATE Problems on Optimization.