Apply advanced machine learning algorithms such as kernel methods, boosting, deep learning, anomaly detection, factorization models, and probabilistic modeling to analyze and extract insights from data.
Upon successfully completing the course, you will be able to:
Learn how to preprocess data for data mining, explore the data before applying data mining techniques, discover association patterns in a dataset, use advanced predictive modeling techniques to solve problems in the real world, Use different advanced ML techniques to summarize data.
Analyze the complexity of these algorithms and use them appropriately to solve problems in the real world within available resources working on advanced modeling techniques like unsupervised learning, hypothesis testing, and experimental design
Usage of the Recommender systems, decision trees, and interpretable models on the data