ML and vision projects I had to do as part of course.
These are projects I had done for my homeworks and assignments and I am putting them here to showcase what I have learned during the course. I do not promote anybody copy these codes for their assignments in case they also have same/similar assignment.
CSE 4309 (Machine Learning) course description: "This course offers an introduction to machine learning. Topics include naive Bayes classifiers, linear regression, linear classificiers, neural networks and backpropagation, kernel methods, decision trees, clustering, and reinforcement learning. A strong programming background is assumed, as well as familiarity with linear algebra (vector and matrix operations), and knowledge of basic probability theory and statistics. "
CSE 4310 (Computer Vision) course description: "This course introduces students to basic concepts and techniques in computer vision. The topics covered include morphological operations, connected component analysis, image filters, edge detection, feature extraction, object detection, object recognition, tracking, gesture recognition, image formation and camera models, calibration, and stereo vision. A strong programming background is assumed, as well as familiarity with linear algebra (vector and matrix operations), and knowledge of basic probability theory and statistics. "