Launching into Machine Learning

Starting from a history of machine learning, we discuss why neural networks today perform so well in a variety of problems. We then discuss how to set up a supervised learning problem and find a good solution using gradient descent. This involves creating datasets that permit generalization; we talk about methods of doing so in a repeatable way so as to support experimentation.

Starting from a history of machine learning, we discuss why neural networks today perform so well in a variety of problems. We then discuss how to set up a supervised learning problem and find a good solution using gradient descent. This involves creating datasets that permit generalization; we talk about methods of doing so in a repeatable way so as to support experimentation.

Topics:

• Introduction to Course
• Improve Data Quality and Exploratory Data Analysis
• Practical ML
• Optimization
• Generalization and Sampling
• Summary
• Course Resources