{"id":20683118,"url":"https://github.com/eivindarvesen/transfer-learning-demo","last_synced_at":"2026-04-13T10:32:42.468Z","repository":{"id":70323555,"uuid":"107393580","full_name":"EivindArvesen/transfer-learning-demo","owner":"EivindArvesen","description":"Short demo of transfer learning with Inception v3 and TensorFlow","archived":false,"fork":false,"pushed_at":"2017-11-16T13:35:31.000Z","size":3293,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-10T21:50:03.474Z","etag":null,"topics":["deep-learning","demo","inception","machine-learning","neural-network","notebook","python","tensorflow","transfer-learning"],"latest_commit_sha":null,"homepage":null,"language":"Jupyter 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Inception v3 and TensorFlow in a Jupyter notebook.\n\nMuch of the material is based on Google's Codelab [TensorFlow for Poets](https://codelabs.developers.google.com/codelabs/tensorflow-for-poets)\n\n** If you don't want to set up the project dependencies yourself**, you can view results used in a [presentation](Presentasjon.pdf), with different humanoid species of the Star Trek universe [here](https://github.com/eivind88/transfer-learning-demo/blob/master/Transfer-Learning.ipynb). \n\n## Setup\n\nClone this repo via\n\n```bash\ngit clone --recursive git://github.com/foo/bar.git\n```\n\nor if you've already downloaded it, you *need* to init submodules manually:\n\n```bash\ncd \u003crepo\u003e\ngit submodule update --init --recursive\n```\n\n### Python distribution\n\nInstall the [Miniconda](https://conda.io/miniconda.html) (or [Anaconda](https://www.anaconda.com/download/#macos)) Python distribution.\nThe code has been tested on Python 2.\n\nSet up conda environment via `conda env create -n transfer-learning -f environment.yml`\n\n### Dataset\n\nThe dataset-folder contains two folders:\n\"Train\" should contain subfolders named after the class of images they contain;\n\"Test\" should contain test images from multiple classes (not present in the training data).\n\n\n\nYou will need to build your dataset;\n\nI just used [Fatkun Batch Download Image](https://chrome.google.com/webstore/detail/fatkun-batch-download-ima/nnjjahlikiabnchcpehcpkdeckfgnohf?hl=en) to handle batch downloading from Google image search results.\n\n## Run \n\nRun the notebook:\n\n```bash\n# Activate our Python environment\nsource activate transfer-learning\n\n# Start Jupyter and open the notebook\njupyter 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