{"id":20503167,"url":"https://github.com/curt-park/cs231n_assignments","last_synced_at":"2025-04-13T20:16:06.081Z","repository":{"id":134252277,"uuid":"81350244","full_name":"Curt-Park/cs231n_assignments","owner":"Curt-Park","description":"[Assignments] CS231N: Convolutional Neural Networks for Visual Recognition (2016 \u0026 2017)","archived":false,"fork":false,"pushed_at":"2024-02-12T08:42:25.000Z","size":39717,"stargazers_count":46,"open_issues_count":0,"forks_count":10,"subscribers_count":5,"default_branch":"master","last_synced_at":"2024-11-09T10:38:38.177Z","etag":null,"topics":["convolutional-neural-networks","image-captioning","recurrent-neural-networks","visual-recognition"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/Curt-Park.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":"2017-02-08T16:27:46.000Z","updated_at":"2024-02-12T08:42:31.000Z","dependencies_parsed_at":null,"dependency_job_id":"a9fa6355-f86e-4398-8682-78af4293c2e1","html_url":"https://github.com/Curt-Park/cs231n_assignments","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Curt-Park%2Fcs231n_assignments","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Curt-Park%2Fcs231n_assignments/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Curt-Park%2Fcs231n_assignments/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Curt-Park%2Fcs231n_assignments/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Curt-Park","download_url":"https://codeload.github.com/Curt-Park/cs231n_assignments/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224834685,"owners_count":17377756,"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":["convolutional-neural-networks","image-captioning","recurrent-neural-networks","visual-recognition"],"created_at":"2024-11-15T19:29:33.801Z","updated_at":"2024-11-15T19:29:34.654Z","avatar_url":"https://github.com/Curt-Park.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"Repository for programming assignments of CS231n: Convolutional Neural Networks for Visual Recognition (2016 \u0026 2017).\n\n# 2017\n### [Assignment1](http://cs231n.github.io/assignments2017/assignment1/)\n- Q1: k-Nearest Neighbor classifier (20 points)\n- Q2: Training a Support Vector Machine (25 points)\n- Q3: Implement a Softmax classifier (20 points)\n- Q4: Two-Layer Neural Network (25 points)\n- Q5: Higher Level Representations: Image Features (10 points)\n- Q6: Cool Bonus: Do something extra! (+10 points) - *Not done*\n\n### [Assignment2](http://cs231n.github.io/assignments2017/assignment2/)\n- Q1: Fully-connected Neural Network (25 points)\n- Q2: Batch Normalization (25 points)\n- Q3: Dropout (10 points)\n- Q4: Convolutional Networks (30 points)\n- Q5: PyTorch / TensorFlow on CIFAR-10 (10 points) - **Done both in Pytorch and Tensorflow**\n- Q6: Do something extra! (up to +10 points) - **Done both in Pytorch and Tensorflow**\n  - Extra Credit: VGG-like networks which acheive 79.4% and 78.4% on CIFAR-10 test set in Pytorch and Tensorflow respectively\n\n### [Assignment3](http://cs231n.github.io/assignments2017/assignment3/)\n- Q1: Image Captioning with Vanilla RNNs (25 points)\n- Q2: Image Captioning with LSTMs (30 points)\n- Q3: Network Visualization: Saliency maps, Class Visualization, and Fooling Images (15 points) - **Done both in Pytorch and Tensorflow**\n- Q4: Style Transfer (15 points) - **Done both in Pytorch and Tensorflow**\n- Q5: Generative Adversarial Networks (15 points) - **Done both in Pytorch and Tensorflow**\n  - Extra Credit: InfoGAN (TF), WGAN-GP (TF), WGAN-GP (Pytorch)\n\n\n\n# 2016\n### [Assignment1](http://cs231n.github.io/assignments2016/assignment1/)\n- Q1: k-Nearest Neighbor classifier (20 points)\n- Q2: Training a Support Vector Machine (25 points)\n- Q3: Implement a Softmax classifier (20 points)\n- Q4: Two-Layer Neural Network (25 points)\n- Q5: Higher Level Representations: Image Features (10 points)\n- Q6: Cool Bonus: Do something extra! (+10 points) - *Not done*\n\n   \n\n### [Assignment2](http://cs231n.github.io/assignments2016/assignment2/)\n- Q1: Fully-connected Neural Network (30 points)\n- Q2: Batch Normalization (30 points)\n- Q3: Dropout (10 points)\n- Q4: ConvNet on CIFAR-10 (30 points)\n- Q5: Do something extra! (up to +10 points) - **Built a CNN network which acheives 73.5% on CIFAR-10 test set**\n\n   \n\n### [Assignment3](http://cs231n.github.io/assignments2016/assignment3/)\n- Q1: Image Captioning with Vanilla RNNs (40 points)\n- Q2: Image Captioning with LSTMs (35 points)\n- Q3: Image Gradients: Saliency maps and Fooling Images (10 points)\n- Q4: Image Generation: Classes, Inversion, DeepDream (15 points)\n- Q5: Do something extra! (up to +10 points) - *Not done*\n\n\n\n# Useful Links\n- [Course Home](http://cs231n.stanford.edu/)\n- [Syllabus](http://cs231n.stanford.edu/syllabus.html)\n- [Lecture Note](http://cs231n.github.io/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcurt-park%2Fcs231n_assignments","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcurt-park%2Fcs231n_assignments","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcurt-park%2Fcs231n_assignments/lists"}