Machine learning

Understanding popular ML algorithms with their associated mathematical foundations for appreciating these algorithms. 2. Capability to implement basic algorithms using basic machine learning libraries mostly in python. Gain hands-on experience in applying ML to problems encountered in various domains. In addition, obtain exposure to high-level ML libraries or frameworks such as TensorFlow, PyTorch. 3. Make aware of the role of data in the future of computing, and also in solving real-world problems using machine learning algorithms. 4. Help connect real-world problems to appropriate ML algorithm(s) for solving them. Enable formulating real world problems as machine learning tasks. 5. Appreciate the mathematical background behind popular ML algorithms. 6. Ensure awareness about importance of core CS principles such as algorithmic thinking and systems design in ML

ELECTRICAL