pycaret
azureml-examples
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| pycaret | azureml-examples | |
|---|---|---|
| 5 | 4 | |
| 8,406 | 1,554 | |
| 2.0% | 5.0% | |
| 9.4 | 9.6 | |
| 6 days ago | 4 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | 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.
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.
azureml-examples
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How to deploy ML models on Azure Kubernetes Service (AKS)
If you need a reference on how these files should look, you can get a dummy model, env and scoring script here. Optionally, you can also check out my GitHub for the code used to deploy via the Python SDK v2.
- Best way to run my Python project on Azure
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How to get around "package ‘AzureML’ is not available (for R version 4.0.2) "
It seems like there's a new paradigm for R on Azure that uses Docker and job.yml to tell R how to execute your "vanilla" R code without the need for a package. There are examples here: https://github.com/Azure/azureml-examples/tree/0849cbe797d1d524df9fe9d43ac8b36e75ea34ab/cli/jobs/train/r
- Machine learning in Azure
What are some alternatives?
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.
nlpaug - Data augmentation for NLP
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
MachineLearningNotebooks - Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
Understanding_the_EM_Algorithm - Codes for my blog post "Understanding the EM Algorithm" https://mistylight.github.io/posts/20115/
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.
pedestrian-intent-prediction - Repository for master thesis at the Chalmers University of Technology