cascade VS modeldb

Compare cascade vs modeldb and see what are their differences.

cascade

Lightweight and modular MLOps library targeted at small teams or individuals (by Oxid15)
Machine Learning ML Mlops feature-selection model-selection model-lifecycle Deep Learning
Source Code
oxid15.github.io
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modeldb

Open Source ML Model Versioning, Metadata, and Experiment Management (by VertaAI)
Machine Learning model-management modeldb Mit verta model-versioning
Source Code
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cascade modeldb
9 2
16 1,670
- 0.0%
9.3 9.4
8 days ago 3 days ago
Python Java
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

cascade

Posts with mentions or reviews of cascade. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-12.

modeldb

Posts with mentions or reviews of modeldb. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-12.

What are some alternatives?

When comparing cascade and modeldb you can also consider the following projects:

deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai

NVTabular - NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

powershap - A power-full Shapley feature selection method.

zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

ds2 - Easiest way to use AI models without coding (Web UI & API support)

FeatureHub - The most comprehensive library of AI/ML features across multiple domains. Our goal is to create a dataset that serves as a valuable resource for researchers and data scientists worldwide

polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle

Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]

nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

MLflow - Open source platform for the machine learning lifecycle

clearml - ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

deepchecks - Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

cascade vs deeplake cascade vs NVTabular cascade vs powershap cascade vs zenml cascade vs ds2 cascade vs FeatureHub cascade vs polyaxon cascade vs Activeloop Hub cascade vs nni cascade vs MLflow cascade vs clearml cascade vs deepchecks