{"id":17676915,"url":"https://github.com/tapishr/numpy-rnn","last_synced_at":"2026-04-30T11:33:51.577Z","repository":{"id":151542955,"uuid":"119214028","full_name":"tapishr/numpy-RNN","owner":"tapishr","description":"Implementation of an RNN using numpy library in python","archived":false,"fork":false,"pushed_at":"2018-02-01T02:54:30.000Z","size":278,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-10-28T19:40:23.180Z","etag":null,"topics":["numpy","python","recursive-neural-network","rnn"],"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":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tapishr.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":"2018-01-28T00:18:34.000Z","updated_at":"2018-02-01T02:52:44.000Z","dependencies_parsed_at":null,"dependency_job_id":"9f3ee477-17ae-47a6-9626-a775e1a54532","html_url":"https://github.com/tapishr/numpy-RNN","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/tapishr/numpy-RNN","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tapishr%2Fnumpy-RNN","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tapishr%2Fnumpy-RNN/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tapishr%2Fnumpy-RNN/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tapishr%2Fnumpy-RNN/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tapishr","download_url":"https://codeload.github.com/tapishr/numpy-RNN/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tapishr%2Fnumpy-RNN/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32463892,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-29T22:27:22.272Z","status":"online","status_checked_at":"2026-04-30T02:00:05.929Z","response_time":57,"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":["numpy","python","recursive-neural-network","rnn"],"created_at":"2024-10-24T07:27:06.925Z","updated_at":"2026-04-30T11:33:46.566Z","avatar_url":"https://github.com/tapishr.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# numpy-RNN\nThis project contains the implementation of a Recursive Neural Network (RNN) in Python using only numpy and no other high level machine learning/neural network APIs or libraries. It is the first in a series of projects, and is developed with an aim to gain a deeper understanding of the fundamental concepts involved in designing and training RNNs.\n\nIn this project, a RNN is trained on a corpus of characters to enable it to predict the next character given previous characters.\n\n## Dependencies\nOnly 3 dependecies for the code - \n- Python 2.7\n- numpy\n- jupyter\n\n## Instructions\nInstall Jupyter notebooks, navigate to the directory containing `numpy-RNN.ipynb` in the command terminal and run the notebook by typing - \n\n`$ jupyter notebook numpy-RNN.ipynb`\n\nThis will open the notebook in a browser. Execute each cell in the notebook one by one.\n\n## Usage\nThis code was written using [Andrej Karpathy's](https://gist.github.com/karpathy/d4dee566867f8291f086) code, and his [blog post](http://karpathy.github.io/2015/05/21/rnn-effectiveness/).\n\n## Licence\nCopyright (c) 2016, Damien Henry\nAll rights reserved.\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n\n- Redistributions of source code must retain the above copyright notice, this\n  list of conditions and the following disclaimer.\n\n- Redistributions in binary form must reproduce the above copyright notice,\n  this list of conditions and the following disclaimer in the documentation\n  and/or other materials provided with the distribution.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\nAND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\nIMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE\nDISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE\nFOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL\nDAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR\nSERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER\nCAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,\nOR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE\nOF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftapishr%2Fnumpy-rnn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftapishr%2Fnumpy-rnn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftapishr%2Fnumpy-rnn/lists"}