{"id":13471856,"url":"https://github.com/Machine-Learning-Tokyo/DL-workshop-series","last_synced_at":"2025-03-26T15:30:39.723Z","repository":{"id":33524920,"uuid":"158768944","full_name":"Machine-Learning-Tokyo/DL-workshop-series","owner":"Machine-Learning-Tokyo","description":"Material used for Deep Learning related workshops for Machine Learning Tokyo (MLT)","archived":false,"fork":false,"pushed_at":"2023-12-20T01:35:58.000Z","size":15711,"stargazers_count":937,"open_issues_count":1,"forks_count":254,"subscribers_count":66,"default_branch":"master","last_synced_at":"2025-03-13T19:52:34.882Z","etag":null,"topics":["cnn-keras","convolutional-neural-networks","deep-learning","keras","workshop"],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Machine-Learning-Tokyo.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2018-11-23T02:05:44.000Z","updated_at":"2025-01-11T03:35:19.000Z","dependencies_parsed_at":"2024-10-30T02:50:55.709Z","dependency_job_id":null,"html_url":"https://github.com/Machine-Learning-Tokyo/DL-workshop-series","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/Machine-Learning-Tokyo%2FDL-workshop-series","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Machine-Learning-Tokyo%2FDL-workshop-series/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Machine-Learning-Tokyo%2FDL-workshop-series/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Machine-Learning-Tokyo%2FDL-workshop-series/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Machine-Learning-Tokyo","download_url":"https://codeload.github.com/Machine-Learning-Tokyo/DL-workshop-series/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245681175,"owners_count":20655146,"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":["cnn-keras","convolutional-neural-networks","deep-learning","keras","workshop"],"created_at":"2024-07-31T16:00:49.817Z","updated_at":"2025-03-26T15:30:38.833Z","avatar_url":"https://github.com/Machine-Learning-Tokyo.png","language":"Jupyter Notebook","readme":"# DL-workshop-series\nCode used for Deep Learning related workshops for **Machine Learning Tokyo (MLT)**\n\n# Part I: Convolution Operations\n\n## Implementation\n[**ConvKernels**](https://github.com/Machine-Learning-Tokyo/DL-workshop-series/blob/master/Part%20I%20-%20Convolution%20Operations/ConvKernels.ipynb \"ConvKernels\"): colab notebook with simple examples of various kernels applied on an image using convolution operation\n[**ConvNets**](https://github.com/Machine-Learning-Tokyo/DL-workshop-series/blob/master/Part%20I%20-%20Convolution%20Operations/ConvNets.ipynb \"ConvNets\"): colab notebook with functions for constructing keras models.\nModels:\n1. AlexNet\n2. VGG\n3. Inception\n4. MobileNet\n5. ShuffleNet\n6. ResNet\n7. DenseNet\n8. Xception\n9. Unet\n10. SqueezeNet\n11. YOLO\n12. RefineNet\n\n## Slides\nLink to the presentation: https://drive.google.com/open?id=1sXztx3E9M3G0BIRLh6sxaqVOEOdJVJTrzHOixA5b-rM\n\nCheat Sheet: ![Alt text](https://github.com/Machine-Learning-Tokyo/DL-workshop-series/blob/master/Part%20I%20-%20Convolution%20Operations/ConvOpsCheatSheet.png?raw=true \"Cheat Sheet: Conv. Operations\")\n\n## Video series: CNN Architectures (including implementation)\n\n[![YouTube Playlist](https://github.com/Machine-Learning-Tokyo/DL-workshop-series/blob/master/Part%20I%20-%20Convolution%20Operations/CNN_architectures.png)](https://www.youtube.com/playlist?list=PLaPdEEY26UXywkvfCy0tmRoQorSSTfYq3)\n\n# Part II: Learning in Deep Networks\n\n[![YouTube Playlist](https://github.com/Machine-Learning-Tokyo/DL-workshop-series/blob/master/Part%20II%20-%20Learning%20in%20Deep%20Networks/DL_series.png)](https://www.youtube.com/playlist?list=PLaPdEEY26UXxvlzz485w61W4LgO0lUZfg \"Lerning in Deep Networks Video Series\")\n","funding_links":[],"categories":["Jupyter Notebook"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMachine-Learning-Tokyo%2FDL-workshop-series","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FMachine-Learning-Tokyo%2FDL-workshop-series","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMachine-Learning-Tokyo%2FDL-workshop-series/lists"}