Top 23 Python scikit-learn Projects
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
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Dask: Distributed data frames, machine learning and more
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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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Efficiency Ignoring the feature engineering aspects aside, a typical data scientist workflow involves trying out the different models. Some of the AutoML modules like H2O AutoML, AutoSklearn does this for you, and allow you to interpret your models. All these save so much time experimenting with the standard models.
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SKTime
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Project mention: What will the data science job market be like in 5 years? | reddit.com/r/datascience | 2021-08-14
Some AutoML is getting pretty good, AutoGluon is very solid for tabular data. That being said you still need to have your data in tabular format and deployment still requires some effort.
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Project mention: Any interesting open projects to join? Or anyone want with some good ideas want to start one? | reddit.com/r/Python | 2021-02-05
I have contributed to Yellowbrick in the past. https://github.com/DistrictDataLabs/yellowbrick/
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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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"On the simpler side". Do you mean with a graphical interface? Then, orange would be a nice solution. https://orangedatamining.com/
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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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adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Project mention: adversarial-robustness-toolbox: Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams | reddit.com/r/blueteamsec | 2021-12-26 -
ONNX opens an avenue for direct inference using a number of languages and platforms. For example, a model could be run directly on Android to limit data sent to a third party service. ONNX is an exciting development with a lot of promise. Microsoft has also released Hummingbird which enables exporting traditional models (sklearn, decision trees, logistical regression..) to ONNX.
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mars
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
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m2cgen
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
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mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Project mention: I'm Looking to Help Contribute, I am very confident with my skills | reddit.com/r/Python | 2021-12-02Automated Machine Learning (AutoML) Python package https://github.com/mljar/mljar-supervised You can check list of open issues. Or I can recommend some just tell me your preferences (Im the main contributor)
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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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kmodes
Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data
They were probably looking for K-modes
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Project mention: Survival analysis built on top of scikit-learn | reddit.com/r/learnmachinelearning | 2021-03-24
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AlphaPy
Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost
Project mention: AlphaPy: machine learning framework built on sklearn and pandas. Support pyfolio/xgboost/lightgmb/catboost(gradient boosting on decision tress) etc. Examples include financial market prediction/sports prediction/kaggle. Configurations are set though | reddit.com/r/algoprojects | 2021-12-11 -
iterative-stratification
scikit-learn cross validators for iterative stratification of multilabel data
Project mention: TypeError: unhashable type: 'list' when preparing index of labels for MultiLabelBinarizer | reddit.com/r/CodingHelp | 2021-03-31I need to create this so I can encode the Labels and run iterative stratification as detailed [here](https://github.com/trent-b/iterative-stratification). Once I have the index prepared, i will run MultiLabelBinarizer to encode the "Labels" list and create a matrix of those values. I will then run the stratification sampling algorithm on that matrix to determine zero-based train and test indices. The code I have below is causing an error.
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AutoViz
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Project mention: AutoViz: Automatically visualize any dataset, any size with one line of code | news.ycombinator.com | 2021-02-09 -
With the onnxmltools library, traditional models from scikit-learn, XGBoost and others can be exported to ONNX and loaded with txtai. Additionally, Hugging Face's trainer module can train generic PyTorch modules. This notebook will walk through all these examples.
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SciKit-Learn Laboratory
SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments. (by EducationalTestingService)
Python scikit-learn related posts
- GitHub - rodrigo-arenas/Sklearn-genetic-opt: Hyperparameters tuning and feature selection, using evolutionary algorithms.
- New Python AutoML Package
- Improving xgb prediction times on a single core
- Good python time series libraries?
- [OC] Pandemic Impact on Used Honda Civic Prices
- AlphaPy: machine learning framework built on sklearn and pandas. Support pyfolio/xgboost/lightgmb/catboost(gradient boosting on decision tress) etc. Examples include financial market prediction/sports prediction/kaggle. Configurations are set though
- AlphaPy: machine learning framework built on sklearn and pandas. Support pyfolio/xgboost/lightgmb/catboost(gradient boosting on decision tress) etc. Examples include financial market prediction/sports prediction/kaggle. Configurations are set though
Index
What are some of the best open-source scikit-learn projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | data-science-ipython-notebooks | 22,327 |
| 2 | Dask | 9,424 |
| 3 | best-of-ml-python | 6,188 |
| 4 | auto-sklearn | 5,978 |
| 5 | sktime | 4,833 |
| 6 | autogluon | 4,071 |
| 7 | yellowbrick | 3,477 |
| 8 | orange | 3,237 |
| 9 | igel | 2,963 |
| 10 | adversarial-robustness-toolbox | 2,741 |
| 11 | hummingbird | 2,723 |
| 12 | mars | 2,336 |
| 13 | m2cgen | 1,992 |
| 14 | mljar-supervised | 1,747 |
| 15 | modAL | 1,570 |
| 16 | traingenerator | 1,126 |
| 17 | kmodes | 956 |
| 18 | scikit-survival | 710 |
| 19 | AlphaPy | 697 |
| 20 | iterative-stratification | 619 |
| 21 | AutoViz | 612 |
| 22 | onnxmltools | 596 |
| 23 | SciKit-Learn Laboratory | 527 |
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