Top 23 Python AI Projects
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SpaCy is one of the most popular NLP libraries, and is very fast and flexible.
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pytorch-lightning
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
Project mention: [D] Are you using PyTorch or TensorFlow going into 2022? | reddit.com/r/MachineLearning | 2021-12-14Is the problem the sheer number of options, or the fact that they are all together in one place? Would it be better if they were organized into the different trainer entrypoints (fit, validate, ...)? If that is the case, there was an RFC proposing this which you might find interesting, feel free to drop by and comment on the issue: https://github.com/PyTorchLightning/pytorch-lightning/issues/10444
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SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
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Try to use a version controls tool for ML such as DVC
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Fixed Link: https://mycroft.ai/
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cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
Project don't need to be 100% original, do the project in a such a way that other people has not done yet. There are plenty of datasets and notebooks available on Kaggle. Those are just bunch of notebooks. Take the inspiration from the notebook and build the project in modular structure and organize your project in proper folders and modules. I am using this cookiecutter for building my portfolio projects. https://github.com/drivendata/cookiecutter-data-science
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OPS
OPS - Build and Run Open Source Unikernels. Quickly and easily build and deploy open source unikernels in tens of seconds. Deploy in any language to any cloud.
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Project mention: Best job scheduler in 2022? (Airflow / Dagster / Prefect / Luigi / other) | reddit.com/r/dataengineering | 2022-01-18
Can I give a plug for Metaflow. It's particularly well suited to data science and ML workflows, with great tooling that's basically just annotations on python functions that gives you: - DAG orchestration - parallelism - cloud integration - data flow through DAGs — very very useful imo for data science teams trying to migrate their existing scripts to (and write new ones on) Metaflow
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Project mention: [D] AI Background Removal: a quick comparison between RVM & BGMv2 | reddit.com/r/MachineLearning | 2021-10-10
GitHub
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Project mention: [D] A hand-picked selection of the best Python ML Libraries of 2021 | reddit.com/r/MachineLearning | 2021-12-21
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Activeloop Hub
Dataset format for AI. Build, manage, & visualize datasets for deep learning. Stream data real-time to PyTorch/TensorFlow & version-control it. https://activeloop.ai (by activeloopai)
Project mention: The hand-picked selection of the best Python libraries released in 2021 | reddit.com/r/Python | 2021-12-21Hub.
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In this article, we will learn how to create a simple e-commerce search API with multiple platform support: eBay and Amazon. AutoScraper and FastAPi provide the ability to create a powerful JSON API for the date. With Playwright's help, we'll extend our scraper and avoid blocking by using ScrapingAnt's web scraping API.
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haystack
:mag: Haystack is an open source NLP framework that leverages Transformer models. It enables developers to implement production-ready neural search, question answering, semantic document search and summarization for a wide range of applications.
Project mention: Show HN: Hello – A conversational search engine powered by transformers | news.ycombinator.com | 2022-01-14 -
Project mention: Can I use ESP32-Cam to post MQTT with Tensorflow Lite Person Detection? | reddit.com/r/esp32 | 2022-01-20
You probably don't need to run detection on every frame. Frigate for example only typically analyzes at 5 FPS, which is plenty. Having an detector that so quickly flips between on and off isn't super useful either
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Using a general-purpose framework such as FastAPI involves writing a lot of boilerplate code just to get your API endpoint up and running. If deploying a model for a demo is the only thing you are interested in and you do not mind losing some flexibility, you might want to use a specialized serving framework instead. One example is BentoML, which will allow you to get an optimized serving endpoint for your model up and running much faster and with less overhead than a generic web framework. Framework-specific serving solutions such as Tensorflow Serving and TorchServe typically offer optimized performance but can only be used to serve models trained using Tensorflow or PyTorch, respectively.
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Project mention: [D] Productionalizing machine learning pipelines for small teams | reddit.com/r/MachineLearning | 2021-08-08
For running experiments, http://polyaxon.com/ is a really good free open-source package that has lots of nice integrations so you can quickly run experiments in k8s but it might be overkill in some cases.
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clearml
ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
Project mention: [D] Drop your best open source Deep learning related Project | reddit.com/r/MachineLearning | 2021-12-30Hi there. ClearML is our open-source solution which is part of the PyTorch ecosystem. We would really appreciate it if you read our README and starred us if you like what you see!
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Project mention: Automagica VS ClointFusion - a user suggested alternative | libhunt.com/r/automagica | 2021-09-24
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Project mention: good examples of functional-like python code that one can study? | reddit.com/r/functionalprogramming | 2021-06-29
thinc - defining neural nets in functional way jax, a new deep learning framework puts emphasis on functions rather than tensors, I've tested it for a couple of applications and it's really cool, you can write stuff like you'd write math expressions in papers using numpy. That speeds up development significantly, and makes code much more readable
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Project mention: The Kilobyte's Gambit: Can you beat 1024 bytes of JavaScript [at chess]? | news.ycombinator.com | 2021-03-07
Incomprehensible scheiße code. I looked around and I like this one because it has "meta-level" definition of movements and liitle bit of strategy. You could implement context-free chess games with varying rules for us congenitally lazy and dull-witted. https://github.com/thomasahle/sunfish/blob/master/sunfish.py
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Project mention: Has anyone worked on problems involving "portfolio optimization theory"? | reddit.com/r/datascience | 2021-07-29
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Project mention: When to go for an 'easy' time-series model vs. using a complex deep learning model (when having experience with the latter) | reddit.com/r/datascience | 2021-11-29
I'm a data trainee at this organisation. I wrote my master thesis about using an event clustering mechanism to enrich an existing dataset to improve short-term demand predictions, using Pytorch Forecasting using the temporal fusion transformer component, and LightGBM (and compare the models with and w/o the event feature, so 4 runs in total).
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AIF360
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Project mention: Building a Responsible AI Solution - Principles into Practice | dev.to | 2022-01-10Besides the existing monitoring solution mentioned in the section above, we were also took inspiration from continuous integration and continuous delivery (CI/CD) testing tools like Jenkins and Circle CI, on the engineering front, and existing fairness libraries like Microsoft's Fairlearn and IMB's Fairness 360, on the machine learning side of things.
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Index
What are some of the best open-source AI projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | spaCy | 22,176 |
| 2 | pytorch-lightning | 17,009 |
| 3 | MLflow | 11,064 |
| 4 | bert-as-service | 9,823 |
| 5 | dvc | 9,134 |
| 6 | mycroft-core | 5,565 |
| 7 | cookiecutter-data-science | 5,334 |
| 8 | metaflow | 5,178 |
| 9 | RobustVideoMatting | 5,113 |
| 10 | snorkel | 4,996 |
| 11 | Activeloop Hub | 4,200 |
| 12 | autoscraper | 4,184 |
| 13 | haystack | 3,750 |
| 14 | frigate | 3,750 |
| 15 | BentoML | 3,132 |
| 16 | polyaxon | 2,980 |
| 17 | clearml | 2,932 |
| 18 | Automagica | 2,617 |
| 19 | thinc | 2,437 |
| 20 | sunfish | 2,269 |
| 21 | eiten | 2,195 |
| 22 | pytorch-forecasting | 1,665 |
| 23 | AIF360 | 1,612 |
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