VevestaX
bodywork-pymc3-project
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VevestaX | bodywork-pymc3-project | |
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10 | 1 | |
27 | 13 | |
- | - | |
0.0 | 5.3 | |
over 1 year ago | almost 2 years ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | MIT License |
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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MLflow VS VevestaX - a user suggested alternative
2 projects | 12 May 2022
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VevestaX - An awesome and simple tool to track ML experiments in an excel file
We have developed a tool that documents and tracks the evolution of Data science projects. No more fretting over what experiment was rejected and why. We are looking for early adopters to get their generous and valuable feedback. Please DM us or mail us at [email protected] for early access to the tool. Find us at www.vevesta.com
You can check out the source code at our GitHub page: https://github.com/Vevesta/VevestaX.
bodywork-pymc3-project
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A tutorial on how to handle prediction uncertainty in production systems, by using Bayesian inference and probabilistic programs
All of the code is hosted in a GitHub repo, that you can use as a template for your own projects.
What are some alternatives?
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Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
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.
mlflow-easyauth - Deploy MLflow with HTTP basic authentication using Docker
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
amazon-sagemaker-examples - Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
feast - Feature Store for Machine Learning
strava-analysis - 🏃📊 Using strava to do personal analyses and to practice data scientist skills.