Tensors have been increasingly used in data-intensive fields such as artificial intelligence and quantum computing. This course covers the notations, optimization and statistical methods of tensor computation, and their applications in machine learning (mainly deep learning) and quantum computing.

Prerequisites: Solid background in linear algebra and statitics/probability, basic programing skills.

4

Units

Letter

Grading

1, 2, 3

Passtime

Graduate students only

Level Limit

Engineering

College
ZHANG Z
Zheng Zhang
12 reviews
Lecture
PHELP1431
T R
12:30 PM - 13:45 PM
30 / 30 Full
ECE 273 Zhang Z Fall 2023 Total: 11
ECE 273 Zhang Z Fall 2022 Total: 13
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ECE15A . Zhang Z 1 Year, 1 Month Ago

As both a former student and TA for this class, the best advice I can give is to take advantage of his lecture material. If you don't like his lecture style, his slides are extremely thorough and helpful to have up when doing your hw alongside the textbook. Yes it's a lot of work, but once things click you can solve problems at a much faster pace.

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ECE15A . Zhang Z 2 Years Ago

Everything was open notes so was relatively easy. Do all the homework and make sure you have a good grasp on the material and you'll be fine. Quizzes and tests are time crunch but got good curve.

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ECE15A . Zhang Z 2 Years Ago

This professor sent an email at 11:37 pm the day before our midterm to tell us whether or not the test will be online. My advice to anyone who wants to take this class is to be prepared for these type of situations. He's a decent professor, but please be wary that he might procrastinate sending important information regarding midterms & finals.

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ECE15A . Zhang Z 3 Years Ago

Wasn't a very good lecturer; I just read the slides instead of going to class. Class material was a bit daunting at first but not too bad once you get the hang of it. 2 midterms and a final each with one bonus problem. The TAs grade pretty harshly so be careful. 3 quizzes in your TA section.

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