pneumonia_detection
ludwig
pneumonia_detection | ludwig | |
---|---|---|
2 | 3 | |
13 | 10,827 | |
- | 1.0% | |
0.0 | 9.5 | |
almost 2 years ago | 8 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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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
ludwig
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Show HN: Toolkit for LLM Fine-Tuning, Ablating and Testing
This is a great project, little bit similar to https://github.com/ludwig-ai/ludwig, but it includes testing capabilities and ablation.
questions regarding the LLM testing aspect: How extensive is the test coverage for LLM use cases, and what is the current state of this project area? Do you offer any guarantees, or is it considered an open-ended problem?
Would love to see more progress toward this area!
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Python projects with best practices on Github?
Two random examples I found from 30 seconds of googling: Here’s Netflix using it in their crisis management tool, and here’s Uber using it in their deep learning framework.
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Most Frequent 600 Coding Questions on LeetCode
They list themselves all over the internet as an "open source contributor" to Uber, which as far I can tell is based entirely on... reporting that there was an issue with a favicon. To me, it seems like they'll be cheating anybody who employs them based on this, ahem, "experience". And that feels like the tip of the iceberg.
What are some alternatives?
imbalanced-regression - [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
nlp-recipes - Natural Language Processing Best Practices & Examples
streamlit - Streamlit — A faster way to build and share data apps.
data-structures-and-algorithms - Resources that I used to crack some big tech & startups interviews
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
aimet - AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.
datasets - 🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
ai-deadlines - :alarm_clock: AI conference deadline countdowns
Python_Storage_Tracker - Py Storage Tracker is a cross-platform command line tool using Python to track storage and other system related information.
autonlp - 🤗 AutoNLP: train state-of-the-art natural language processing models and deploy them in a scalable environment automatically