IEEE CS- Machine Learning – Data Science Series

The first session of the Machine Learning and Data Science series conducted by IEEE Computer Society together with FOSS Cell CET, was held on the 5th of May 2017. The session, handled by Nirmal and Amrith, was open to non-IEEE members as well.

The session was started off by Nirmal, wherein he introduced the two hot buzzwords – Machine Learning and Artificial Intelligence. He explained the concept of giving machines access to data and letting them learn for themselves. He gave a brief insight into the ‘perfect AI’ and then proceeded to explain the two major divisions of machine learning – supervised and unsupervised. Linear regression and classification, which are the subcategories of supervised machine learning, were dealt in detail.

Amrith joined in explaining the cost function in linear regression and the gradient descent, which is a numerical optimization algorithm. They made use of several graphical representations effectively. Being a hands-on session, the attendees were made to try out the python program for optimizing linear regression with gradient descent.

The session came to an end by 6pm. Amrith gave a brief description on the topics that are to be covered in the upcoming sessions of the Machine Learning series. The feedback on the day’s session was collected from the attendees.