jupyter-annotate
best-of-ml-python
jupyter-annotate | best-of-ml-python | |
---|---|---|
1 | 16 | |
14 | 15,672 | |
- | 2.8% | |
0.0 | 7.8 | |
almost 2 years ago | 5 days ago | |
TypeScript | Python | |
BSD 3-clause "New" or "Revised" License | Creative Commons Attribution Share Alike 4.0 |
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.
jupyter-annotate
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[P] Text annotator for entity extraction that runs in your notebook
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
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Ask HN: How to get back into AI?
For Python, here's a nice compilation: https://github.com/ml-tooling/best-of-ml-python/blob/main/RE...
- Best-Of Machine Learning with Python
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Questions regarding Job Requirements for data analyst to data science transition?
You will need numpy, scipy, pandas, scikit-learn, Keras/tensorflow/pytorch, xgboost and many many many others. See this list for example.
- Awesome list of ML
- Are there any speech recognition modules so I can write one and do not have to rely on google and the likes?
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Learning opencv
Take a look at this list on github. It has a pretty comprehensive list of python image libraries.
- Best-of Machine Learning with Python
- 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
What are some alternatives?
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.