Machine Learning

Description

In this course, you will learn :

• Build and train supervised models for prediction and binary classification tasks using NumPy and scikit-learn (linear, logistic regression).
• Create and train a neural network in TensorFlow to perform multi-class classification, as well as create and use decision trees and tree ensemble methods.
• Use best practises for machine learning development and unsupervised learning techniques such as clustering and anomaly detection.
• Create recommender systems using a collaborative filtering approach and a deep learning method based on content, as well as a deep reinforcement learning model.

Syllabus :

• Supervised Machine Learning: Regression and Classification
• Advanced Learning Algorithms
• Unsupervised Learning, Recommenders, Reinforcement Learning