Regularization Learning

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI.

This course provides a high-level overview of the most important concepts in machine learning and econometrics.

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

Master machine learning by doing it in practice, using an automated machine learning GUI that requires little/no coding.

Master the MLA-C01 AWS Machine Learning Engineer Exam: SageMaker, Bedrock, and AI Skills for Certification Success!

Master machine learning by doing it in practice, using an automated machine learning GUI that requires little/no coding.

Machine Learning in practice with Python’s own scikit-learn on real-world datasets!

Master deep learning from mathematical foundations to hands-on model deployment—everything in one unique course!

Build 30+ ML Projects in 30 Days in AWS, Master SageMaker JumpStart, Canvas, AutoPilot, DataWrangler, Lambda & S3