fnn
pycaret
| fnn | pycaret | |
|---|---|---|
| 1 | 5 | |
| 118 | 8,428 | |
| - | 1.2% | |
| 1.8 | 9.4 | |
| almost 3 years ago | 5 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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.
fnn
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[R] PhD & postdoc positions at UT Austin: ML for complex systems (chaotic time series, cellular automata, & fluid dynamics)
Code for https://arxiv.org/abs/2002.05909 found: https://github.com/williamgilpin/fnn
pycaret
- pycaret: An open-source, low-code machine learning library in Python
- Predictive Maintenance and Anomaly Detection Resources
- Pycaret
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How to look for help on data science?
Take a look at Pycaret python library. https://github.com/pycaret/pycaret
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What is your DS stack? (and roast mine :) )
If you want to try pycaret exists, not sure how similar it is to caret, but it does all the steps in ML project. And Gluon for DL.
What are some alternatives?
tsfresh - Automatic extraction of relevant features from time series:
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
neuralforecast - Scalable and user friendly neural :brain: forecasting algorithms.
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
cellular-automata-pytorch - A reproduction and tweaking of Growing Neural Cellular Automata
ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
dspytai - EVMOS blockchain Dapp that utilizes on-chain data to model potential price fluctuations in real-time from covalent api.
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Twitter-sentiment-analysis - A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.
azureml-examples - Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.