Description:
In the past decade, we have observed the expeditious evolution and tremendous applications of machine learning, such as unmanned vehicles, autonomous language translation, and smart healthcare. This course will introduce the fundamental knowledge of machine learning techniques via a series of hands-on real-world examples in Python. The overall aim is to provide the students with a good understanding of machine-learning technologies, building machine learning with Python, and applying machine-learning technologies to address real-world problems. In the course projects, students will also have an opportunity to explore cutting-edge machine-learning technologies and develop their own machine-learning-based solutions.
Topics covered: Machine Learning, Linear and Logistic Regressions, Fully-Connected Neural Networks, Convolutional Neural Network, Recurrent Neural Network, Autoencoders, Generative Adversarial Network, Deep Reinforcement Learning Models, Emerging Topics.