Applications of Machine Learning

Delivered tutorials and graded assignments on key machine learning topics including supervised, unsupervised (clustering), reinforcement learning, fairness and bias, neural networks, computer vision, and natural language processing (NLP). Designed hands-on programming demos using “PyTorch, TensorFlow, and Keras” in Python, helping students apply theoretical concepts to real-world problems.