ESE 4170
Introduction to Machine Learning and Pattern Classification
This course provides a broad introduction to machine learning and statistical pattern classification. Students will study theoretical foundations of learning and several important supervised and unsupervised machine learning methods and algorithms, including linear model of regression and classification, logistic regression, Bayesian learning methods, neural networks, nearest neighbor method, support vector machines methods, clustering methods and principal component analysis. Students will also learn to use Python programming language to implement learned models and methods to solve pattern classification problems.
Instructors
Reviews
Terrible lecturer and an extremely harsh grader. Will take 10 points off your quiz for a single notation.
10/29/2024
Terrible lecturer who does a horrible job at explaining concepts. Extremely harsh grader who will take points off based on grading criteria that were never specified.
10/15/2024
I can tell he really tried at the beginning, and it turned out that the first few lectures were great. Then he ended up literally reading off the slides.
9/12/2024
So many unanswered Piazza posts. He put in some effort and tried to explain the concepts but just ended up reading from the slides. Open book/notes for quizzes and exams and you can get most answers from following the slides examples.
7/1/2024
Dr Zhang is a strict grader and all of his quizzes don't have any reference to what is taught in his class. His lectures can get boring because he reads off of the lecture slides.
5/18/2024
Seldom answer students questions on piazza Tough grader on quiz
5/15/2024
He simply doesn't care about his students. He rarely answers Piazza questions and assignment instructions are vague. TAs also aren't helpful. Programming sessions are useless.
5/14/2024
Seldom answer the students' questions on piazza. Give the marks according on his mood and distribution line. A liitle bit of stubborn on his teaching level. In summary, do not choose him except no choices.
5/12/2024
Prof. Zhang needs to work on two things. \n1) Fixing his lecture slides so that they are readable and let alone understandable. You spend most of your time in class trying to decipher the information on slides rather than learning any ideas and connecting them. \n2) Figuring out more relevant ways to test us on machine learning concepts.
4/23/2024
Lectures left much to be desired as he read off slides, and if the projector died, he wouldn't fix it. Little to no examples were provided during the lectures, making the quizzes and homework challenging. There were sparse guidelines for the final project but a lot of expectations for style, content, etc.
12/19/2023
Overall, a good professor. Concepts are illustrated clearly in the lecture slides.
5/16/2022
Simply reads off of the slides. Gives very vague answers to piazza posts. Once class was over, he sent a random email at 9 am in the morning stating that you need to send in a proof that you completed course evaluations now as he is entering the grades, rather than giving students more time to send the proof. I saw the email only 2 hours late.
5/12/2022
Jinsong Zhang is not only a bad teacher but is also incredibly not nice. His lecture notes are incredibly opaque, and his notation is often awful and inconsistent. It would be ok if he was willing to be more helpful out of class, but instead he is rude and unhelpful. I spent most of my time learning from other sources online. What a waste of time.
10/27/2021