{"id":22052825,"url":"https://github.com/srking501/csc8637_coursework","last_synced_at":"2026-05-04T02:40:40.347Z","repository":{"id":226644333,"uuid":"769262586","full_name":"Srking501/csc8637_coursework","owner":"Srking501","description":"A summative coursework for CSC8637 Deep Learning ","archived":false,"fork":false,"pushed_at":"2024-03-08T17:41:55.000Z","size":10717,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-23T15:39:20.774Z","etag":null,"topics":["ai","cyclegan","data-preprocessing","data-science","evaluation-metrics","fine-grained-classification","gan","gans","generative-adversarial-network","image-classification","lstm","lstm-classification","rnn","rnn-lstm","rnn-tensorflow","time-series","timeseries","timeseries-forecasting"],"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/Srking501.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}},"created_at":"2024-03-08T17:18:47.000Z","updated_at":"2024-06-07T16:54:58.000Z","dependencies_parsed_at":"2024-03-08T18:57:46.562Z","dependency_job_id":null,"html_url":"https://github.com/Srking501/csc8637_coursework","commit_stats":null,"previous_names":["srking501/csc8637_coursework"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Srking501/csc8637_coursework","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Srking501%2Fcsc8637_coursework","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Srking501%2Fcsc8637_coursework/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Srking501%2Fcsc8637_coursework/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Srking501%2Fcsc8637_coursework/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Srking501","download_url":"https://codeload.github.com/Srking501/csc8637_coursework/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Srking501%2Fcsc8637_coursework/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32592720,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-03T22:12:39.696Z","status":"online","status_checked_at":"2026-05-04T02:00:06.625Z","response_time":58,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["ai","cyclegan","data-preprocessing","data-science","evaluation-metrics","fine-grained-classification","gan","gans","generative-adversarial-network","image-classification","lstm","lstm-classification","rnn","rnn-lstm","rnn-tensorflow","time-series","timeseries","timeseries-forecasting"],"created_at":"2024-11-30T15:14:22.614Z","updated_at":"2026-05-04T02:40:40.321Z","avatar_url":"https://github.com/Srking501.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# CSC8637 Deep Learning\n\nThe CycleGAN model is from:-\n\n* https://keras.io/examples/generative/cyclegan/\n\n```bibtex\n@inproceedings{CycleGAN2017,\n  title={Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks},\n  author={Zhu, Jun-Yan and Park, Taesung and Isola, Phillip and Efros, Alexei A},\n  booktitle={Computer Vision (ICCV), 2017 IEEE International Conference on},\n  year={2017}\n}\n```\n\nThe datasets used:-\n\nFor Task 1 CycleGAN:\n* UTK Face Cropped: https://www.kaggle.com/datasets/abhikjha/utk-face-cropped\n* Inceptionv3: https://www.kaggle.com/code/bmarcos/image-recognition-gender-detection-inceptionv3/data\n* Dog Face Dataset: https://images.cv/dataset/dog-face-image-classification-dataset\n* Cat Dataset: https://www.kaggle.com/datasets/spandan2/cats-faces-64x64-for-generative-models\n\nFor Task 2 Fine-grained image classification:\n* https://www.kaggle.com/datasets/seryouxblaster764/fgvc-aircraft/code\n\nFor Task 3 is a dataset made by the University:-\n\nThe file is a comma separated value (CSV) file with the following columns:\n* Date and time of the event\n* The event type – either LOGIN or LOGOUT\n* The cluster on which the event occurred\n* The duration – for a LOGIN this is the number of milli-seconds the user was logged in for, for a LOGOUT this is zero\n* The total number of users logged in at that point in time","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsrking501%2Fcsc8637_coursework","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsrking501%2Fcsc8637_coursework","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsrking501%2Fcsc8637_coursework/lists"}