https://github.com/yash1994/auto-awesome-list

:zap: An automated list of Machine Learning and Data Science tools from research organizations
https://github.com/yash1994/auto-awesome-list

artificial-intelligence big-data data-science machine-learning

Last synced: 4 months ago
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:zap: An automated list of Machine Learning and Data Science tools from research organizations

• Host: GitHub
• URL: https://github.com/yash1994/auto-awesome-list
• Owner: yash1994
• Created: 2020-02-10T15:15:55.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2020-07-09T12:04:07.000Z (over 5 years ago)
• Last Synced: 2024-12-02T20:02:01.599Z (about 1 year ago)
• Topics: artificial-intelligence, big-data, data-science, machine-learning
• Language: Python
• Size: 597 KB
• Stars: 4
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-automl - yash1994/auto-awesome-list

README

          
# :dizzy: Auto-Awesome-List

Auto-awesome-list is auto generated list of machine learning and data science tool from research organizations. Sometimes its easy and reasonable to use pre-implemented tool instead of re-enventing the wheel. This module uses [Github API V3](https://developer.github.com/v3/) with keywords defined in `topics.list` (common github topics used in ML and DS tools) and `tasks.list` (list of ML and AI tasks) filter the tools. These lists will get updated every month. New organization can simply be added to `watch.list` with `organization name,gituhb orgainzation url` format. Suggestions and pull request are always welcomed. :blush:

Inspired by [Papers With Code](https://paperswithcode.com/) and [Awesome](https://github.com/sindresorhus/awesome).

Note: Lists contains some stats for every tool repository. These stats may be wrong because information is not getting fecthed in real-time.

## List of Organizations

[Microsoft](data/microsoft.md), [IBM](data/ibm.md), [NVIDIA](data/nvidia.md), [DeepMind](data/deepmind.md), [H2O.ai](data/h2o.ai.md), [Google](data/google.md), [Explosion.ai](data/explosion.ai.md), [Google-Research](data/google-research.md), [Spotify](data/spotify.md), [OpenAI](data/openai.md), [Salesforce](data/salesforce.md), [Intel](data/intel.md), [Uber](data/uber.md), [Hugging-Face](data/hugging-face.md), [Alibaba](data/alibaba.md), [Lyft](data/lyft.md), [Adobe](data/adobe.md), [Pytorch](data/pytorch.md), [Allenai](data/allenai.md), [Oracle](data/oracle.md), [Eclipse](data/eclipse.md), [Netflix](data/netflix.md), [eBay](data/ebay.md), [Baidu](data/baidu.md), [Airbnb](data/airbnb.md), [Intuit](data/intuit.md), [Stanford-NLP](data/stanford-nlp.md), [Amazon](data/amazon.md), [Twitter](data/twitter.md), [Keras](data/keras.md), [Fastai](data/fastai.md), [Facebook](data/facebook.md), [Tensorflow](data/tensorflow.md), [VMware](data/vmware.md), [PayPal](data/paypal.md), [Baidu-Research](data/baidu-research.md), [RARE-Technologies](data/rare-technologies.md), [SAP](data/sap.md), [Fizyr](data/fizyr.md), [Tesla](data/tesla.md), [Snap](data/snap.md)

## Analysis of Machine Learning / Data Science Tools

![distribution_of_programming_languages](plots/distribution_of_programming_languages.svg)

![portion_of_data_science___machine_learning_tools_over_all_repos](plots/portion_of_data_science___machine_learning_tools_over_all_repos.svg)

![distribution_of_stars](plots/distribution_of_stars.svg)

![repositories_created_over_time](plots/repositories_created_over_time.svg)

![repositories_updated_over_time](plots/repositories_updated_over_time.svg)

![common_data_science_tasks](plots/common_data_science_tasks.svg)

## Todos

- [x] Add more non profit organizations.

- [x] Add analysis based on repositories

- [ ] Add task based classification.