Supervised and Deep Learning Lab

 

Subject Code- ML 463P

Introduction

The lab focuses on key steps in supervised learning, including data preprocessing, feature selection, model training, evaluation, and tuning. By the end of the lab, participants will have a solid understanding of how to build, train, and optimize supervised learning models for various applications, from predicting outcomes to classifying data.

 

Objective of the Laboratory

• To analyse basic concepts of probability and linear algebra
• To understand various aspects of self-learning.
• To introduce students to the fundamentals of Supervised Learning and Deep Learning techniques and algorithms.

  Facilities

    Software: Anaconda

  People

    Faculty Coordinator: Dr. Preeti

    Lab Technician:  Mrs. Yashoda Rani