472 Open source projects that are alternatives of or similar to Awesome Production Machine Learning

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".

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Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.

For calculating global feature importance using Shapley values.

Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

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Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

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Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

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Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

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A curated list of awesome machine learning interpretability resources.

A Python package implementing a new machine learning model for text classification with visualization tools for Explainable AI

[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

This project provides responsible AI user interfaces for Fairlearn, interpret-community, and Error Analysis, as well as foundational building blocks that they rely on.

Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/

H2O.ai Machine Learning Interpretability Resources

Code for the paper "BIOLITMAP: a web-based geolocated and temporal visualization of the evolution of bioinformatics publications" in Oxford Bioinformatics.

Introduction to Data Science

потоковый курс "Машинное обучение и анализ данных (Machine Learning and Data Mining)" на факультете ВМК МГУ имени М.В. Ломоносова

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[ICCV 2017] Torch code for Grad-CAM

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

pyclustring is a Python, C++ data mining library.

moDel Agnostic Language for Exploration and eXplanation

MetaSRA: normalized sample-specific metadata for the Sequence Read Archive

Interpretability Methods for tf.keras models with Tensorflow 2.x

Data collection tool for social media analytics

Automatic equation building and curve fitting. Runs on Tensorflow. Built for academia and research.

General Interpretability Package

Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.

The easiest way to automate your data

IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018

Extract structured data from PDF invoices

Learn how to responsibly deliver value with ML.

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

PHP-ML - Machine Learning library for PHP

The Subdue graph miner discovers highly-compressing patterns in an input graph.

Federated Learning Library: https://fedml.ai

A proofreader for your data

CleverCSV is a Python package for handling messy CSV files. It provides a drop-in replacement for the builtin CSV module with improved dialect detection, and comes with a handy command line application for working with CSV files.

NFStream: a Flexible Network Data Analysis Framework.

Label Studio is a multi-type data labeling and annotation tool with standardized output format

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Python Data Science and Machine Learning Library for the Ethereum and ERC-20 Blockchain

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Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

ELKI Data Mining Toolkit

The Ruby DataMining Gem, is a little collection of several Data-Mining-Algorithms

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