Top 15 Python machine-learning-algorithm Projects
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nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Project mention: Automated Machine Learning (AutoML) - 9 Different Ways with Microsoft AI | dev.to | 2021-10-04For a complete tutorial, navigate to this Jupyter Notebook: https://github.com/microsoft/nni/blob/master/examples/notebooks/tabular_data_classification_in_AML.ipynb
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Machine-Learning-Collection
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
Project mention: Pytorch: Custom Dataset for Machine Translation | reddit.com/r/learnpython | 2022-04-08seq2seq_attention
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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cleanlab
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels
Project mention: Is the hardest part of writing code for machine learning data collection? | reddit.com/r/learnmachinelearning | 2022-05-12And to extend u/mgmillem's answer on automation a little more, there is a rising number of tools out there to help automate/speed up/simplify this process. One of them is cleanlab which automatically finds and fixes label errors in any ML classification dataset. We've open-sourced it here: https://github.com/cleanlab/cleanlab, it's free to use, so give it a go! hope this helps!
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igel
a delightful machine learning tool that allows you to train, test, and use models without writing code
Project mention: Train/fit, test, and use models without writing code | reddit.com/r/ArtificialInteligence | 2021-06-29Link to the repo: https://github.com/nidhaloff/igel
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Project mention: Launch HN: Lightly (YC S21): Label only the data which improves your ML model | news.ycombinator.com | 2021-08-09
How does it differentiate from modAL?
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Just like Photoshop, GIMP is only capable of fast and complex editing with the help of brushes(here are some good ones), scripts and sometimes plugins(also this one is recommended, available on most distro's repos as both standalone or as a plugin).
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SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
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Project mention: [R] apd-crs: Cure Rate Survival Analysis in Python | reddit.com/r/MachineLearning | 2022-01-31
The typical reason you would go with a weibull function is if you want to be able to relax proportional hazard like in this work: https://github.com/ragulpr/wtte-rnn
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AlgorithmsAndDataStructure
Algorithms And DataStructure Implemented In Python & CPP, Give a Star 🌟If it helps you
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scikit-learn-intelex
Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application
Project mention: Machine Learning with PyTorch and Scikit-Learn – The *New* Python ML Book | news.ycombinator.com | 2022-02-25 -
Machine-Learning
Implementation of different ML Algorithms from scratch, written in Python 3.x (by Gautam-J)
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pretty-print-confusion-matrix
Confusion Matrix in Python: plot a pretty confusion matrix (like Matlab) in python using seaborn and matplotlib
Project mention: Trying to understand an Index Error Message | reddit.com/r/learnpython | 2022-02-18I am attempting to use the pretty-print confusion-matrix library to create a confusion matrix.
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Project mention: Multi label classification on sparse labels | reddit.com/r/learnmachinelearning | 2021-09-09
Code: https://github.com/amzn/pecos
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If anyone is interested, I have two projects that uses k-means
https://github.com/victorqribeiro/groupImg
https://github.com/victorqribeiro/budget
Being one of the first ML algorithms that I learned, I spend some time finding use cases for it
If I'm not mistaken I've also used in to classify deforestation in an exercise
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Project mention: I have coded a machine learning algorithm and trained it to recreate the Reddit Snoo | reddit.com/r/Logos | 2022-01-15
Python machine-learning-algorithms related posts
- Introduction to K-Means Clustering
- Machine Learning with PyTorch and Scikit-Learn – The *New* Python ML Book
- [R] apd-crs: Cure Rate Survival Analysis in Python
- Improving xgb prediction times on a single core
- Intel Extension for Scikit-Learn
- Multi label classification on sparse labels
- Train/fit, test, and use models without writing code
Index
What are some of the best open-source machine-learning-algorithm projects in Python? This list will help you:
Project | Stars | |
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1 | nni | 11,461 |
2 | Machine-Learning-Collection | 3,547 |
3 | cleanlab | 3,348 |
4 | igel | 2,980 |
5 | tslearn | 2,109 |
6 | modAL | 1,687 |
7 | GIMP-ML | 1,051 |
8 | wtte-rnn | 702 |
9 | AlgorithmsAndDataStructure | 612 |
10 | scikit-learn-intelex | 547 |
11 | Machine-Learning | 399 |
12 | pretty-print-confusion-matrix | 379 |
13 | pecos | 295 |
14 | groupImg | 191 |
15 | visualisa | 0 |
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