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30-days-of-python

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.

aix360

Interpretability and explainability of data and machine learning models

anomaly-detection-using-k-means-clustering

azureml-snippets

VSCode snippets for Azure Machine Learning

bert4doc-classification

Code and source for paper ``How to Fine-Tune BERT for Text Classification?``

captum

Model interpretability and understanding for PyTorch

causalnex

A Python library that helps data scientists to infer causation rather than observing correlation.

cqr

Conformalized Quantile Regression

dalex

moDel Agnostic Language for Exploration and eXplanation

deep_learning_prediction_intervals

ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'

driverlessai-recipes

Recipes for Driverless AI

drwhy

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

EvalML is an AutoML library written in python.

exbert

A Visual Analysis Tool to Explore Learned Representations in Transformers Models

google-research

Google Research

h2o-3

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.

hackerrank

Solutions to HackerRank problems

interpret

Fit interpretable models. Explain blackbox machine learning.

jalammar.github.io

Build a Jekyll blog in minutes, without touching the command line.

keras-tuner

knime-python

KNIME Python Integration

kubernetes-the-hard-way

Bootstrap Kubernetes the hard way on Google Cloud Platform. No scripts.

learn-python

📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.

machine_learning_refined

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

machinelearningnotebooks

Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

mixture-density-networks-for-distribution-and-uncertainty-estimation

A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)

ml-on-gcp

Machine Learning on Google Cloud Platform

mlbox

MLBox is a powerful Automated Machine Learning python library.

nonconformist

Python implementation of the conformal prediction framework.

numpydl

Deep Learning Library. For education. Based on pure Numpy. Support CNN, RNN, LSTM, GRU etc.