Bigdataanalytics_infoh515
Material for the Big Data Analytics exercise classes - INFOH515 - Big Data : Distributed Data Management and Scalable Analytics - Université Libre de Bruxelles
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Clearml Server | 338 | 3 months ago | 89 | other | Python | |||||
| ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, ML-Ops and Data-Management | ||||||||||
| Keras Sharp | 248 | 3 years ago | 22 | other | C# | |||||
| An ongoing effort to port the Keras deep learning library to C#, supporting both TensorFlow and CNTK | ||||||||||
| Fglab | 207 | 6 years ago | 14 | mit | HTML | |||||
| Future Gadget Laboratory | ||||||||||
| Model Sdk | 101 | 5 | 2 years ago | 92 | December 23, 2020 | 10 | mit | Python | ||
| 💥🐍 Runway Model SDK: port your own machine learning models to Runway | ||||||||||
| Katana Assistant | 88 | a year ago | 19 | apache-2.0 | JavaScript | |||||
| Text based assistant powered by Machine Learning and NLP | ||||||||||
| Deepnet | 84 | 5 years ago | 4 | apache-2.0 | F# | |||||
| Deep.Net machine learning framework for F# | ||||||||||
| Flask Angular Data Science | 74 | 6 years ago | 1 | TypeScript | ||||||
| Repository for a data science starter app using Flask, Angular and Docker. https://medium.com/@dvelsner/deploying-a-simple-machine-learning-model-in-a-modern-web-application-flask-angular-docker-a657db075280 | ||||||||||
| Bigdataanalytics_infoh515 | 56 | 2 years ago | Jupyter Notebook | |||||||
| Material for the Big Data Analytics exercise classes - INFOH515 - Big Data : Distributed Data Management and Scalable Analytics - Université Libre de Bruxelles | ||||||||||
| Convnetswift | 43 | 7 years ago | mit | Swift | ||||||
| Swift port of ConvnetJS. [Work in progress] | ||||||||||
| Deploy Ml Model | 33 | 5 years ago | 1 | mit | Jupyter Notebook | |||||
| Deploying a simple machine learning model to an AWS ec2 instance using flask and docker. | ||||||||||
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