Course Structure
The course will be conducted in a hands-on manner. Each class will start with a lecture where a topic will be discussed. The students will then complete the exercises related to the topic.
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About the course
The course will provide a quick introduction to Python and the theoretical foundations of basic concepts in machine learning and artificial intelligence. We will look into the following topics in detail"
- Linear and Logistic Regression
- Simple Neural Networks
- Convolutional Neural Network
- Deep Learning
We will cover both the theoretical aspects and practical implementation of these algorithms on small scale problems.
Theoretical Setup
Derivation of the detailed setup of Artificial Intelligence and Machine Learning algorithms
Coding the Algorithms
Setup of Artificial Intelligence and Machine Learning algorithm in Python and Python based packages (PyTorch, TensorFlow)
Hands-on Exercise
A set of exericese to understand and merge the theoretical and practical aspects of Artificial Intelligence and Machine Learning algortihms.