jupyter-annotate VS best-of-ml-python

Compare jupyter-annotate vs best-of-ml-python and see what are their differences.

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jupyter-annotate best-of-ml-python
1 16
14 15,633
- 2.6%
0.0 7.8
almost 2 years ago 7 days ago
TypeScript Python
BSD 3-clause "New" or "Revised" License Creative Commons Attribution Share Alike 4.0
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.

jupyter-annotate

Posts with mentions or reviews of jupyter-annotate. We have used some of these posts to build our list of alternatives and similar projects.
  • [P] Text annotator for entity extraction that runs in your notebook
    1 project | /r/MachineLearning | 15 Aug 2022
    Hi! We have just open-sourced our text annotator which runs directly in your notebook. You can now select spans of text for entity extraction and do your processing & modelling all in the same place. This allows for quick iteration when getting a project started. Here is the repository: https://github.com/dataqa/jupyter-annotate.

best-of-ml-python

Posts with mentions or reviews of best-of-ml-python. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-10.

What are some alternatives?

When comparing jupyter-annotate and best-of-ml-python you can also consider the following projects:

responsible-ai-toolbox - Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

Awesome-WAF - 🔥 Web-application firewalls (WAFs) from security standpoint.

kubeflow - Machine Learning Toolkit for Kubernetes

ktrain - ktrain is a Python library that makes deep learning and AI more accessible and easier to apply

dtale - Visualizer for pandas data structures

ffcv - FFCV: Fast Forward Computer Vision (and other ML workloads!)

awesome-python - An opinionated list of awesome Python frameworks, libraries, software and resources.

kmodes - Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data

NBA-Machine-Learning-Sports-Betting - NBA sports betting using machine learning

livelossplot - Live training loss plot in Jupyter Notebook for Keras, PyTorch and others

speechbrain - A PyTorch-based Speech Toolkit

VeRyPy - A python library with implementations of 15 classical heuristics for the capacitated vehicle routing problem.