{"id":17352518,"url":"https://github.com/lucko515/tesla-stocks-prediction","last_synced_at":"2025-04-14T20:31:17.251Z","repository":{"id":104742875,"uuid":"99617195","full_name":"lucko515/tesla-stocks-prediction","owner":"lucko515","description":"The implementation of LSTM in TensorFlow used for the stock prediction.","archived":false,"fork":false,"pushed_at":"2020-01-07T20:10:35.000Z","size":622,"stargazers_count":59,"open_issues_count":2,"forks_count":42,"subscribers_count":9,"default_branch":"master","last_synced_at":"2025-03-28T09:01:54.142Z","etag":null,"topics":["deep-learning","lstm-neural-networks","machine-learning","rnn-tensorflow","stock-price-prediction","tensorflow"],"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":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lucko515.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":"2017-08-07T20:25:32.000Z","updated_at":"2025-03-21T16:06:41.000Z","dependencies_parsed_at":null,"dependency_job_id":"7de5080a-1084-4e1f-9bed-ef4e5008b0fb","html_url":"https://github.com/lucko515/tesla-stocks-prediction","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/lucko515%2Ftesla-stocks-prediction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lucko515%2Ftesla-stocks-prediction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lucko515%2Ftesla-stocks-prediction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lucko515%2Ftesla-stocks-prediction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lucko515","download_url":"https://codeload.github.com/lucko515/tesla-stocks-prediction/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248955509,"owners_count":21189139,"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":["deep-learning","lstm-neural-networks","machine-learning","rnn-tensorflow","stock-price-prediction","tensorflow"],"created_at":"2024-10-15T17:13:57.935Z","updated_at":"2025-04-14T20:31:17.235Z","avatar_url":"https://github.com/lucko515.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Predicting Tesla stock prices with RNNs\n\nThis is an example on how to use RNNs to predict stock market price.\n\nI've used LSTM as a type of RNN.\n\n![](lstm_cell.png)\n*This LSTM cell image is from [Colah's blog.](http://colah.github.io/posts/2015-08-Understanding-LSTMs/)*\n\n## Dataset\n\nThe dataset used in this project is Tesla stocks history (From August 2014 - August 2017). I have downloaded this file from Google stocks, but you have *csv* file inside the project folder. Name of the file is **tesla_stocks.csv**.\n\n## Install\n\n### \u0026nbsp;\u0026nbsp;\u0026nbsp; Supported Python version\n\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;- Python version used in this project: 3.5+\n\n### \u0026nbsp;\u0026nbsp;\u0026nbsp; Libraries used\n\n\u003e *  [Pandas](http://pandas.pydata.org) 0.18.0\n\u003e *  [Numpy](http://www.numpy.org) 1.10.4\n\u003e *  [Matplotlib](https://matplotlib.org) 1.5.1\n\u003e *  [Scikit-learn](http://scikit-learn.org/stable/) 0.17.1\n\u003e *  [TensorFlow](https://www.tensorflow.org) 1.2.0\n\n## Code\n\nThis project has 2 different implementations.\n\n1. Implementation by using Tensorflow built-in RNN functions. This is a version which you would use in an industry. This implementation can be found inside **tensorflow_lstm.ipynb**.\n\n2.  Implementation number 2 has been done without using any high level functions from TensorFlow. This implementation is good for understanding how RNNs are working. This implementations is in file **lstm_from_scratch_tensorflow.ipynb**.\n\n## Run\n\nTo run this project you will need some software, like Anaconda, which provides support for running .ipynb files (Jupyter Notebook).\n\nAfter making sure you have that, you can run from a terminal or cmd next lines:\n\nFor the 1st version of the code:\n\n`ipython notebook tensorflow_lstm.ipynb`\n\nor\n\n`jupyter notebook tensorflow_lstm.ipynb`\n\nFor the 2nd version of the code:\n\n`ipython notebook lstm_from_scratch_tensorflow.ipynb`\n\nor\n\n`jupyter notebook lstm_from_scratch_tensorflow.ipynb`\n\n\n## License\n\nIT License\n\nCopyright (c) 2017 Luka Anicin\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flucko515%2Ftesla-stocks-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flucko515%2Ftesla-stocks-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flucko515%2Ftesla-stocks-prediction/lists"}