Linking pages
- Apache Arrow and the "10 Things I Hate About pandas" - Wes McKinney https://wesmckinney.com/blog/apache-arrow-pandas-internals/ 143 comments
- Amazon’s Exabyte-Scale Migration from Apache Spark to Ray on Amazon EC2 | AWS Open Source Blog https://aws.amazon.com/blogs/opensource/amazons-exabyte-scale-migration-from-apache-spark-to-ray-on-amazon-ec2/ 90 comments
- quokka/why.md at master · marsupialtail/quokka · GitHub https://github.com/marsupialtail/quokka/blob/master/blog/why.md 78 comments
- GitHub - josephmisiti/awesome-machine-learning: A curated list of awesome Machine Learning frameworks, libraries and software. https://github.com/josephmisiti/awesome-machine-learning 58 comments
- GitHub - Ly0n/awesome-robotic-tooling: Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace https://github.com/Ly0n/awesome-robotic-tooling 54 comments
- statsforecast/README.md at main · Nixtla/statsforecast · GitHub https://github.com/Nixtla/statsforecast/blob/main/experiments/neuralprophet/README.md 42 comments
- GitHub - vinta/awesome-python: A curated list of awesome Python frameworks, libraries, software and resources https://github.com/vinta/awesome-python 38 comments
- Ray: A Distributed Framework for Emerging AI Applications https://www.micahlerner.com/2021/06/27/ray-a-distributed-framework-for-emerging-ai-applications.html 34 comments
- 10x Faster Parallel Python Without Python Multiprocessing | by Robert Nishihara | Towards Data Science https://towardsdatascience.com/10x-faster-parallel-python-without-python-multiprocessing-e5017c93cce1 29 comments
- GitHub - fugue-project/fugue: A unified interface for distributed computing. Fugue executes SQL, Python, and Pandas code on Spark, Dask and Ray without any rewrites. https://github.com/fugue-project/fugue 23 comments
- GitHub - Nixtla/statsforecast: Lightning ⚡️ fast forecasting with statistical and econometric models. https://github.com/Nixtla/statsforecast 22 comments
- GitHub - wwxFromTju/awesome-reinforcement-learning-lib: GitHub's code repository is all you need https://github.com/wwxFromTju/awesome-reinforcement-learning-lib 19 comments
- GitHub - Officium/RL-Experiments: High-quality implementations of deep reinforcement learning algorithms for experiments https://github.com/Officium/RL-Experiments 14 comments
- statsforecast/experiments/arima_prophet_adapter at main · Nixtla/statsforecast · GitHub https://github.com/Nixtla/statsforecast/tree/main/experiments/arima_prophet_adapter 14 comments
- GitHub - mikeroyal/Neuromorphic-Computing-Guide: Learn about the Neumorphic engineering process of creating large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures. https://github.com/mikeroyal/Neuromorphic-Computing-Guide 7 comments
- Writing your First Distributed Python Application with Ray | by Michael Galarnyk | Towards Data Science https://towardsdatascience.com/writing-your-first-distributed-python-application-with-ray-4248ebc07f41 7 comments
- GitHub - smorad/popgym: Partially Observable Process Gym http://github.com/smorad/popgym 7 comments
- Parallelizing Python Code. This article reviews some common… | by Michael Galarnyk | Towards Data Science https://towardsdatascience.com/parallelizing-python-code-3eb3c8e5f9cd 6 comments
- Why Learn Python Concurrency - Super Fast Python https://superfastpython.com/why-learn-python-concurrency/ 6 comments
- quokka/release.md at master · marsupialtail/quokka · GitHub https://github.com/marsupialtail/quokka/blob/master/blog/release.md 5 comments
Linked pages
- [1712.05889] Ray: A Distributed Framework for Emerging AI Applications https://arxiv.org/abs/1712.05889 15 comments
- [1703.03924] Real-Time Machine Learning: The Missing Pieces https://arxiv.org/abs/1703.03924 0 comments
- [2203.05072] Exoshuffle: Large-Scale Shuffle at the Application Level https://arxiv.org/abs/2203.05072 0 comments
- [1712.09381] RLlib: Abstractions for Distributed Reinforcement Learning http://arxiv.org/abs/1712.09381 0 comments