VevestaX
mlflow-easyauth
Our great sponsors
| VevestaX | mlflow-easyauth | |
|---|---|---|
| 10 | 1 | |
| 27 | 100 | |
| - | 1.0% | |
| 0.0 | 3.0 | |
| over 1 year ago | 9 months ago | |
| Jupyter Notebook | Shell | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
VevestaX
-
📝Everything you need to know about Distributed training and its often untold nuances
100 early birds who login into www.vevesta.com will get a free lifetime subscription.
- [D] Open Source library to do automatic EDA + experiment tracking in a spreadsheet
-
[D] ZIP models as a means to handle regression on data with excess of zeros
Sharing an article on how to handle regression for data which has lots and lots of zeros. VevestaX/ZIP_tutorial.md at main · Vevesta/VevestaX · GitHub
- Zero Inflated Poisson Regression Model – How to model data with lot of zeroes?
-
MLflow VS VevestaX - a user suggested alternative
2 projects | 12 May 2022
- Show HN: Discover VevestaX – Track ML features, experiments and EDA in an Excel
-
[D] Impactful Computer Vision Research - Nerf (Neural Radiance Fields)
On side note, we have developed a knowledge repository for Machine Learning Projects with note taking ability. We are looking for beta testers. Check us out on www.vevesta.com or mail us on [[email protected]](mailto:[email protected]). Eager to hear your views on the same.
-
VevestaX - An awesome and simple tool to track ML experiments in an excel file
You can check out the source code at our GitHub page: https://github.com/Vevesta/VevestaX.
-
VevestaX - Library to track ML experiments and data into an excel file
Gitlink: https://github.com/Vevesta/VevestaX
mlflow-easyauth
-
hosted/managed MLFlow?
Not fully managed, but we put https://github.com/soundsensing/mlflow-easyauth on Heroku. Heroku manages the OS, database and application lifecycle, logging etc. Much more comfortable than dealing with VMs
What are some alternatives?
bodywork-pipeline-with-aporia-monitoring - Integrating Aporia ML model monitoring into a Bodywork serving pipeline.
create-react-app-buildpack - ⚛️ Heroku Buildpack for create-react-app: static hosting for React.js web apps
MLOps - End to End toy example of MLOps
mlflow-tracking-server - This repository hosts the code to make it easier to deploy a customizable and flexible MLflow tracking server solution to your Kubernetes cluster.
vertex-ai-samples - Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud
flytesnacks - Flyte Documentation 📖
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
awesome-kubernetes - A curated list for awesome kubernetes sources :ship::tada:
mlflow-deployments - Source code for the post Effortless deployments with MLFlow, showcasing how logging models using MLFLow can provide you want to easily deploy them in production later.
Dokku - A docker-powered PaaS that helps you build and manage the lifecycle of applications
OAD - Collection of tools and scripts useful to automate microscopy workflows in ZEN Blue using Python and Open Application Development tools and AI tools.
recommenders - Best Practices on Recommendation Systems