Applied Machine Learning
What is machine 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
What is CS229A?
This class' emphasis is on Applied Machine Learning. Concretely, we want
to give you the practical skills needed to get learning algorithms
Compared to CS229 (Machine Learning), we cover fewer learning algorithms,
and also spend less time on the math and theory of machine learning, but spend much
more time on the pratical, hands-on skills (and "dirty tricks") for getting this
stuff to work well on an application. More of the homeworks will also focus on
giving you practice implementing, modifying and debugging learning algorithms,
and less on the mathematical underpinnings of machine learning.
How will this class work?
This is an online and largely self-paced class, and the majority
of the class content will be delivered via online videos. Even though there is a regular class meeting time where
we will discuss machine learning and extensions to the course material,
most of the in-person Monday meetings are optional.
How can I find out more about the class?
Additional information is on the Course Information page.
Common questions are also answered on the FAQ page.
How do I sign up?
Please sign up on Axess, and come to
the first meeting on September 26th. Because this is the first time we're
offering this class, enrollment is limited (tentatively to about 30
students). If the class is oversubscribed, we may give priority to
students who have not taken and are not currently taking CS229.
3-4 units. Hewlett 103. Mondays 4.15-5.30pm.