Coursera Machine Learning

Welcome to the Reinforcement Learning course. Here you will find out about: - foundations of RL methods: value/policy iteration, q-learning, policy gradient, etc. –- with math & batteries included - using deep neural networks for RL tasks –- also known as "the hype train"

Deep Learning Specialization. Master Deep Learning, and Break into AI

Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars.

Learn about artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We'll emphasize both the basic algorithms and the practical tricks needed to get them to work well.

Kickstart your Career in Data Science & ML. Master data science, learn Python & SQL, analyze & visualize data, build machine learning models.

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework.

Expert in Data Science, Machine Learning and AI. Become an IBM-approved Expert in Data Science, Machine Learning and Artificial Intelligence.

Advance your career in data engineering.

What you'll learn
Perform regression analysis, least squares and inference using regression models.

What you'll learn
Perform regression analysis, least squares and inference using regression models.