pneumonia_detection
datasets
| pneumonia_detection | datasets | |
|---|---|---|
| 2 | 15 | |
| 13 | 18,443 | |
| - | 1.0% | |
| 0.0 | 9.5 | |
| almost 2 years ago | 3 days ago | |
| Python | Python | |
| MIT License | 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.
pneumonia_detection
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Help with resume! Just graduated (:
Same goes for your pneumonia project. Not a hiring manager although if I got asked by my lead to rate an application, I'd say projects you copy from Google are a big minus and if I find an applicants project on google within a minute, I'd have a lot less confidence in said candidate vs. somebody who is out there producing original projects. 1 really good original project is better and more valuable than 2 or 3 projects from tutorials.
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I wanted to try streamlit, so I trained a model to diagnose lung X-Rays (Pneumonia) and visualised it with streamlit [not hosted]
The model had a ~91% accuracy on a 300 image test set. It had the most problems with false positives (which I guess is better then false negatives🤷♂️) --> check confusion matrix in github readme for more
datasets
- 🐍🐍 23 issues to grow yourself as an exceptional open-source Python expert 🧑💻 🥇
- Mastering ROUGE Matrix: Your Guide to Large Language Model Evaluation for Summarization with Examples
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How to Train Large Models on Many GPUs?
https://github.com/huggingface/datasets
https://github.com/huggingface/transformers
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[D] Can we use Ray for distributed training on vertex ai ? Can someone provide me examples for the same ? Also which dataframe libraries you guys used for training machine learning models on huge datasets (100 gb+) (because pandas can't handle huge data).
https://huggingface.co/docs/datasets backed with an Arrow file or buffer
- Need help with a data science project
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Is there a text evaluation metric that does not need reference text?
I'm looking for an automatic evaluation metric that can score the first text higher (since it's more grammatically correct/better for other reasons). All the metrics for NLG I found require some reference text to match the generated text with, which I don't have.
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FauxPilot – an open-source GitHub Copilot server
And then pass that my_code.json as the dataset name.
[1] https://github.com/huggingface/datasets
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Hugging Face Introduces ‘Datasets’: A Lightweight Community Library For Natural Language Processing (NLP)
Code for https://arxiv.org/abs/2109.02846 found: https://github.com/huggingface/datasets
Quick Read | Paper | Github
- Datasets: A Community Library for Natural Language Processing
What are some alternatives?
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
streamlit - Streamlit — A faster way to build and share data apps.
datumaro - Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.
ludwig - Low-code framework for building custom LLMs, neural networks, and other AI models
cypress-realworld-app - A payment application to demonstrate real-world usage of Cypress testing methods, patterns, and workflows.
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
edex-ui - A cross-platform, customizable science fiction terminal emulator with advanced monitoring & touchscreen support.
first-contributions - 🚀✨ Help beginners to contribute to open source projects
frankmocap - A Strong and Easy-to-use Single View 3D Hand+Body Pose Estimator
evaluate - 🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
starter-workflows - Accelerating new GitHub Actions workflows