{"id":19892861,"url":"https://github.com/red-rapious/cs-classes-m1-s1","last_synced_at":"2025-03-01T05:26:14.912Z","repository":{"id":253325907,"uuid":"805736001","full_name":"Red-Rapious/CS-Classes-M1-S1","owner":"Red-Rapious","description":"My Computer Science classes for the first semester (S1) of second year (M1) at ENS Ulm.","archived":false,"fork":false,"pushed_at":"2024-12-19T21:30:36.000Z","size":172245,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-11T19:44:27.495Z","etag":null,"topics":["classes","course"],"latest_commit_sha":null,"homepage":"","language":"TeX","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Red-Rapious.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-25T10:13:38.000Z","updated_at":"2024-12-25T08:42:07.000Z","dependencies_parsed_at":"2024-08-22T22:18:40.734Z","dependency_job_id":"c268e5c9-e91c-4abd-81bd-a7d0c720b311","html_url":"https://github.com/Red-Rapious/CS-Classes-M1-S1","commit_stats":null,"previous_names":["red-rapious/cs-classes-m1-s1"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Red-Rapious%2FCS-Classes-M1-S1","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Red-Rapious%2FCS-Classes-M1-S1/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Red-Rapious%2FCS-Classes-M1-S1/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Red-Rapious%2FCS-Classes-M1-S1/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Red-Rapious","download_url":"https://codeload.github.com/Red-Rapious/CS-Classes-M1-S1/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241321571,"owners_count":19943964,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["classes","course"],"created_at":"2024-11-12T18:25:54.859Z","updated_at":"2025-03-01T05:26:14.894Z","avatar_url":"https://github.com/Red-Rapious.png","language":"TeX","funding_links":[],"categories":[],"sub_categories":[],"readme":"# CS-Classes-M1-S1\nThe class notes of my computer science classes for the first semester of second year (M1) at ENS Ulm.\n\n## Content\nAvailable classes are:\n- [Introduction to Computer Vision (CV)](computer-vision/computer-vision.pdf)\n- [Deep Learning (DL)](deep-learning/deep-learning.pdf)\n- [Robotics (RB)](robotics/robotics.pdf)\n- [Convex Optimization (CO)](convex-optimization/convex-optimization.pdf)\n\n## Progression\nClasses are in active development. Below is a summary of the current availability of chapters. Note that chapter titles for future lectures are subject to modifications.\n\n*The following legend is used:*\n| ***Symbol*** | ***Meaning*** |\n|------------|-------------|\n| :x: | *Not started* |\n| :large_orange_diamond: | *In progress* |\n| :white_check_mark: | *Finished* |\n\n### Computer vision\n| **Chapter Title** | **Progress** |\n|-------------------|--------------|\n| Introduction to Computer Vision | :x: |\n| Camera Geometry | :x: |\n| Camera Calibration | :white_check_mark: |\n| Image Processing | :white_check_mark: |\n| Edge Detection | :white_check_mark: |\n| Image Restoration | :x: |\n| Radiometry and Color | :x: |\n| Stereopsis | :x: |\n| Two-view Geometry | :white_check_mark: |\n| ... | :x: |\n\n### Deep Learning\n| **Chapter Title** | **Progress** |\n|-------------------|--------------|\n| Introduction | :white_check_mark: |\n| Automatic differentiation | :large_orange_diamond: |\n| Deep Reinforcement Learning | :large_orange_diamond: |\n| Optimization and loss functions | :white_check_mark: |\n| Convolutional Neural Networks | :white_check_mark: |\n| Recurrent Neural Networks | :white_check_mark: |\n| Attention and Transformers | :white_check_mark: |\n| Robustness and Regularity | :white_check_mark: |\n| Generative and Autoregressive Models | :white_check_mark: |\n| Autoencoders | :white_check_mark: |\n| Generative Adversarial Neural Networks | :white_check_mark: |\n| Normalizing Flows | :white_check_mark: |\n\n### Robotics\n| **Chapter Title** | **Progress** |\n|-------------------|--------------|\n| Introduction | :x: |\n| Position and Orientation | :white_check_mark: |\n| Forward Kinematics | :white_check_mark: |\n| Inverse Kinematics | :white_check_mark: |\n| Direct and Inverse Dynamics | :white_check_mark: |\n| Motion Planning | :white_check_mark: |\n| Collision Detection | :large_orange_diamond: |\n| Optimal Control | :x: |\n\n### Convex Optimization\n| **Chapter Title** | **Progress** |\n|-------------------|--------------|\n| Introduction | :white_check_mark: |\n| Convex sets | :white_check_mark: |\n| Convex functions | :white_check_mark: |\n| Convex problems | :white_check_mark: |\n| Duality I | :white_check_mark: |\n| Duality II | :white_check_mark: |\n| Base methods for unconstrained optimization | :x: |\n| Constrained optimization | :x: |\n| Splitting methods and monotone operators | :x: |\n| Stochastic methods | :x: |\n\n## Contribution\nContributing to this repository is encouraged: please let me know about typos and suggestions, using the GitHub issue feature or through a PR. Small additions are also welcomed.\n\n## Disclaimer\nDespite being written and organized by me, these documents contain material heavily inspired by my teacher's own classes.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fred-rapious%2Fcs-classes-m1-s1","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fred-rapious%2Fcs-classes-m1-s1","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fred-rapious%2Fcs-classes-m1-s1/lists"}