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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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For Python, here's a nice compilation: https://github.com/ml-tooling/best-of-ml-python/blob/main/RE...
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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Data scientists work on phenomenally large datasets, and Dask is a handy tool for exploration within the confines of a single cloud VM or their local PCs. Location data visualization is an essential part of deciding further algorithm development and roadmap for projects. This lays the foundation for data engineering and science to work at scale, with petabytes of data.
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Project mention: mlcourse.ai: NEW Courses - star count:8584.0 | reddit.com/r/algoprojects | 2023-02-04
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Project mention: Does anyone know a trusted Python package for applying Croston's Time series method? | reddit.com/r/pythontips | 2022-12-04
I initially used the SkTime's Croston class SKTime Croston but when I try to get the fitted values using the steps in the discussion on github, the values are the same, a straight line throughout the in-sample to ou-of-sample predictions.
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Sonar
Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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Only thing I can think of is Orange, which has some statistics capability, but isn't its focus.
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Project mention: [D] DL Practitioners, Do You Use Layer Visualization Tools s.a GradCam in Your Process? | reddit.com/r/MachineLearning | 2022-10-28
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Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
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If are interested in just predictions you can try Hummingbird. It is part of the PyTorch ecosystem. We get already trained scikit-learn models and translate them into PyTorch models. From them you can run your model on any hardware support by PyTorch, export it into TVM, ONNX, etc. Performance on hardware acceleration is quite good (orders of magnitude better than scikit-learn is some cases)
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igel
a delightful machine learning tool that allows you to train, test, and use models without writing code
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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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mljar-supervised
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Project mention: Show HN: AutoML Python Package for Tabular Data with Automatic Documentation | reddit.com/r/hypeurls | 2022-09-05 -
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
Project mention: Redis as a Database — Data Migration With RedisOM, RedisGears and Redlock | dev.to | 2023-01-22Notice that I’m using random values to populate the Sentiment field. You might compute the values for your fields based on other fields or actually use an ML model to perform the transformation. E.g. you could make use of m2cgen to transform trained models to pure python code and load them in **RedisGears **to be executed in a *GearsBuilder *instance. Another option is to pull out the big guns and go straight to RedisAI.
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Project mention: What are frameworks/tools used for Human-In-The-Loop (active) learning ? | reddit.com/r/computervision | 2022-05-23
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Project mention: Scikit-learn Stock Prediction: using fundamental and pricing data to predict future stock returns. Sklearn's randomforest classifier is trainded and author claimed positive live trading results. Not actively mainained Other Models - star count:1367.0 | reddit.com/r/algoprojects | 2023-01-28
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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.
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Machine-Learning-with-Python
Small scale machine learning projects to understand the core concepts . Give a Star 🌟If it helps you. BONUS: Interview Bank coming up..! (by devAmoghS)
Project mention: GitHub - devAmoghS/Machine-Learning-with-Python: Small scale machine learning projects to understand the core concepts . Give a Star 🌟If it helps you. BONUS: Interview Bank coming up..! | reddit.com/r/coolgithubprojects | 2022-04-04 -
kmodes
Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data
Project mention: kmodes, Python package for categorical clustering releases version 0.12.0. Now with sample weighting and Python 3.10 support. | reddit.com/r/datascience | 2022-03-30 -
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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 -
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Python scikit-learn related posts
- Scikit-learn Stock Prediction: using fundamental and pricing data to predict future stock returns. Sklearn's randomforest classifier is trainded and author claimed positive live trading results. Not actively mainained Other Models - star count:1367.0
- Scikit-learn Stock Prediction: using fundamental and pricing data to predict future stock returns. Sklearn's randomforest classifier is trainded and author claimed positive live trading results. Not actively mainained Other Models - star count:1367.0
- Scikit-learn Stock Prediction: using fundamental and pricing data to predict future stock returns. Sklearn's randomforest classifier is trainded and author claimed positive live trading results. Not actively mainained Other Models - star count:1367.0
- Monte Carlo Simulator feature request.
- Scikit-learn Stock Prediction: using fundamental and pricing data to predict future stock returns. Sklearn's randomforest classifier is trainded and author claimed positive live trading results. Not actively mainained Other Models - star count:1367.0
- Scikit-learn Stock Prediction: using fundamental and pricing data to predict future stock returns. Sklearn's randomforest classifier is trainded and author claimed positive live trading results. Not actively mainained Other Models - star count:1367.0
- Scikit-learn Stock Prediction: using fundamental and pricing data to predict future stock returns. Sklearn's randomforest classifier is trainded and author claimed positive live trading results. Not actively mainained Other Models - star count:1367.0
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A note from our sponsor - Sonar
www.sonarsource.com | 9 Feb 2023
Index
What are some of the best open-source scikit-learn projects in Python? This list will help you:
Project | Stars | |
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1 | data-science-ipython-notebooks | 24,602 |
2 | best-of-ml-python | 12,580 |
3 | Dask | 10,716 |
4 | mlcourse.ai | 8,599 |
5 | auto-sklearn | 6,730 |
6 | sktime | 6,094 |
7 | autogluon | 5,301 |
8 | orange | 3,929 |
9 | yellowbrick | 3,902 |
10 | Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials | 3,337 |
11 | hummingbird | 3,085 |
12 | igel | 3,024 |
13 | mars | 2,547 |
14 | mljar-supervised | 2,439 |
15 | m2cgen | 2,375 |
16 | modAL | 1,890 |
17 | MachineLearningStocks | 1,378 |
18 | traingenerator | 1,252 |
19 | AutoViz | 1,202 |
20 | Machine-Learning-with-Python | 1,138 |
21 | kmodes | 1,115 |
22 | scikit-survival | 887 |
23 | scikit-learn-intelex | 885 |