Lecture 3: Data Preprocessing and Feature Engineering
Lecture 4: Supervised Learning
Lecture 5: Unsupervised Learning
Lecture 6: Model Evaluation and Hyperparameter Tuning
Lecture 7: Model Deployment
This course offers a hands-on introduction to machine learning using Python, designed for learners looking to apply machine learning techniques to real-world problems. Participants will explore key concepts such as data preprocessing, feature engineering, and both supervised and unsupervised learning. The course also covers essential topics like model evaluation, hyperparameter tuning, and model deployment. By the end of the course, learners will have the skills to build, evaluate, and deploy machine learning models using Python, making it an ideal choice for aspiring data scientists and machine learning practitioners.
