IT

Neural network implementation and image classification with TensorFlow and Keras, emphasizing deep learning concepts in practical machine learning applications.

Hands-on reinforcement learning with Q-learning implementation in Python, using OpenAI Gym's MountainCar and Cartpole environments for practical learning.

Introduction to Rule Learning in machine learning, focusing on entropy calculation and rule learner implementation using Python on real datasets.

In-depth exploration of Decision Trees in machine learning, focusing on classification, regression, and real-world banking data applications.

Exploring logistic regression and parameter tuning in machine learning with practical Python exercises, focusing on predictive analytics in sports data.

Advanced regression techniques and k-fold Cross Validation in machine learning, focusing on Python implementation and model optimization.

Training regression models in Python, with practical exercises on real-world datasets, emphasizing model development and performance evaluation.

Introduction to Python data tools and exploratory analysis of real-world datasets, emphasizing statistical understanding and visualization techniques.

Real-world group project on developing efficient algorithms for secret key cracking, emphasizing smart computing and algorithmic design skills.