STATS C161
Introduction to Pattern Recognition and Machine Learning
Description: Lecture, three hours. Requisites: course 100B, Mathematics 33A. Introduction to pattern analysis and machine intelligence designed for advanced undergraduate and graduate students. Concurrently scheduled with course C261. P/NP or letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
It helps to have a good foundation in statistics and linear algebra to do some of the math in the homework problems. The class was very helpful in regards to gaining a foundation in the topic. I took it Spring 2014 and he added programming problems to the homeworks, which greatly increased the time it took to the homeworks. The programming problems were applied, i.e. use this to solve this instead of implement this. We could use whatever language we were familiar with. The final was conceptual, so be sure to go over the homeworks and the notes.
It helps to have a good foundation in statistics and linear algebra to do some of the math in the homework problems. The class was very helpful in regards to gaining a foundation in the topic. I took it Spring 2014 and he added programming problems to the homeworks, which greatly increased the time it took to the homeworks. The programming problems were applied, i.e. use this to solve this instead of implement this. We could use whatever language we were familiar with. The final was conceptual, so be sure to go over the homeworks and the notes.
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