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30 days of Python programming challenge is a step by step guide to learn the Python programming language in 30 days. This challenge may take up to 100 days, follow your own pace.
Interpretability and explainability of data and machine learning models
VSCode snippets for Azure Machine Learning
Code and source for paper ``How to Fine-Tune BERT for Text Classification?``
Model interpretability and understanding for PyTorch
A Python library that helps data scientists to infer causation rather than observing correlation.
Conformalized Quantile Regression
moDel Agnostic Language for Exploration and eXplanation
ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'
Recipes for Driverless AI
DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.
EvalML is an AutoML library written in python.
A Visual Analysis Tool to Explore Learned Representations in Transformers Models
Google Research
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.
Solutions to HackerRank problems
Fit interpretable models. Explain blackbox machine learning.
Build a Jekyll blog in minutes, without touching the command line.
KNIME Python Integration
Bootstrap Kubernetes the hard way on Google Cloud Platform. No scripts.
📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
Machine Learning on Google Cloud Platform
MLBox is a powerful Automated Machine Learning python library.
Python implementation of the conformal prediction framework.
Deep Learning Library. For education. Based on pure Numpy. Support CNN, RNN, LSTM, GRU etc.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.