VevestaX
MLflow
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| VevestaX | MLflow | |
|---|---|---|
| 10 | 55 | |
| 27 | 17,234 | |
| - | 2.4% | |
| 0.0 | 9.9 | |
| over 1 year ago | 4 days ago | |
| Jupyter Notebook | Python | |
| 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
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📝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
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[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?
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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
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[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.
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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.
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VevestaX - Library to track ML experiments and data into an excel file
Gitlink: https://github.com/Vevesta/VevestaX
MLflow
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My Favorite DevTools to Build AI/ML Applications!
MLflow is an open-source platform for managing the end-to-end machine learning lifecycle. It includes features for experiment tracking, model versioning, and deployment, enabling developers to track and compare experiments, package models into reproducible runs, and manage model deployment across multiple environments.
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.
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cascade alternatives - clearml and MLflow
3 projects | 1 Nov 2023
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EL5: Difference between OpenLLM, LangChain, MLFlow
MLFlow - http://mlflow.org
- Explain me how websites like Dall-E, chatgpt, thispersondoesntexit process the user data so quickly
- [D] What licensed software do you use for machine learning experimentation tracking?
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Exploring MLOps Tools and Frameworks: Enhancing Machine Learning Operations
MLflow:
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Options for configuration of python libraries - Stack Overflow
In search for a tool that needs comparable configuration I looked into mlflow and found this. https://github.com/mlflow/mlflow/blob/master/mlflow/environment_variables.py There they define a class _EnvironmentVariable and create many objects out of it, for any variable they need. The get method of this class is in principle a decorated os.getenv. Maybe that is something I can take as orientation.
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[D] Is there a tool to keep track of my ML experiments?
I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
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[Q] Is there a tool to keep track of my ML experiments?
Hi, you should have a look at ML flow https://mlflow.org or weight and biases https://wandb.ai/site
What are some alternatives?
bodywork-pipeline-with-aporia-monitoring - Integrating Aporia ML model monitoring into a Bodywork serving pipeline.
clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution
MLOps - End to End toy example of MLOps
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
vertex-ai-samples - Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
guildai - Experiment tracking, ML developer tools
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.
dvc - 🦉 ML Experiments and Data Management with Git
mlflow-easyauth - Deploy MLflow with HTTP basic authentication using Docker
tensorflow - An Open Source Machine Learning Framework for Everyone