Open-source alternatives to Alibi Detect

Debugging, monitoring and visualization for Python Machine Learning and Data Science

keras-vis is a high-level toolkit for visualizing and debugging your trained keras neural net models. Currently supported visualizations include:

Library for exploring and validating machine learning data

Pydantic is a data validation and serialization library that enforces schema constraints and performs type conversion on complex data structures. It utilizes standard Python type annotations to define data models, allowing developers to establish structured schemas that automatically enforce business rules and constraints without the need for custom domain-specific languages. The library distinguishes itself by transforming high-level model definitions into optimized code during initialization to minimize runtime overhead. It supports recursive validation for nested data structures and employ

River is a Python framework for online machine learning, designed to train and evaluate models on streaming data. It enables incremental learning by updating model parameters one observation at a time, eliminating the need to store full training datasets in memory. The library distinguishes itself through a dedicated concept drift detection system that monitors changes in data distributions to trigger model adaptation. It also provides a progressive validation framework that simulates real-time deployment by testing models on samples before using them for training. The system covers a broad

GoLearn is a machine learning library for the Go programming language. It provides a supervised learning framework and a toolkit for building, training, and evaluating predictive models through a standardized interface. The project implements a data frame system that loads CSV files into structured grids for matrix operations. It includes a preprocessing library for discretizing continuous variables and a model evaluation toolkit that utilizes confusion matrices and cross-validation to measure precision and recall. The library covers data engineering and management, including the ability to

Deepchecks is a machine learning model validation framework and MLOps testing library. It serves as an AI data quality suite and performance evaluator designed to verify the integrity and performance of models and datasets from research through production. The project functions as a model monitoring tool for tracking data drift and performance degradation in production environments. It allows for the creation of custom validation suites and utilizes a pluggable check architecture to automate quality checks within continuous integration pipelines. The framework covers a broad range of capabil

Data engineering practice repository providing tutorials, distributed processing engines, and Python data pipeline automation scripts. The system encompasses automated data validation, distributed compute aggregation, embedded columnar querying, lazy evaluation planning, partitioned storage export, and cloud storage retrieval. The capability surface covers cloud integration and storage, data engineering and pipelines, data processing and analytics, data quality and testing, database and storage, file management, and monitoring and observability.

This project is a public health dataset providing historical and real-time COVID-19 case and death counts across the United States. It consists of a collection of CSV files containing time-series pandemic data organized by date, state, and county. The dataset includes specialized records for institutional outbreaks, tracking infection and death rates within correctional facilities, colleges, and universities. It also provides statistics on excess mortality to estimate total pandemic impact and survey-based data on mask usage prevalence across different counties. To facilitate geographic anal

PyCaret is a Python AutoML platform and MLOps lifecycle manager designed to automate machine learning workflows. It functions as a low-code environment that leverages a scikit-learn native engine to execute preprocessing, training, and evaluation for tabular data. The platform distinguishes itself as an LLM-powered ML copilot, using large language model agents to analyze datasets, design experiment configurations, and explain model results. It also serves as a Kubernetes ML orchestrator and model registry, enabling the versioning of trained pipelines and their promotion to production API endp

This project is an open-source customer relationship management platform that functions as a low-code application development framework. It provides a unified interface for tracking sales pipelines, managing customer interactions, and automating lead routing. The platform is built to serve as a business process automation tool, allowing users to define custom data structures and workflows to streamline operational tasks. The system distinguishes itself through its metadata-driven architecture, which enables dynamic form generation and relational document modeling. By utilizing server-side scr

SeaTunnel is a distributed data integration engine designed to synchronize structured and unstructured data across diverse sources and sinks. It functions as a multi-engine execution framework that can run data integration tasks across different distributed computing backends to optimize workload performance. The project is distinguished by a visual data pipeline designer for configuring workflows without manual code and a specialized change data capture tool for streaming incremental database updates. It also includes an enrichment pipeline that integrates large language models and embedding

This is a machine learning educational repository consisting of a collection of notebooks and code examples. It provides practical implementations of diverse machine learning algorithms and workflows, ranging from traditional scientific computing to deep learning. The project features specific implementations of Scikit-Learn models, such as decision trees, random forests, and support vector machines, as well as TensorFlow examples for building neural networks, convolutional layers, and recurrent architectures. It also includes tutorials on reinforcement learning development and the creation o

Abseil is a common utility library for C++ that provides foundational building blocks for applications. It serves as a collection of optimized utility functions and data structures that augment the C++ standard library across different compiler versions. The library is distinguished by its high-performance containers, including SIMD-accelerated hash maps and sets for efficient key-value lookups. It also provides a comprehensive framework for computing absolute time points, durations, and timestamps across global time zones. The project covers a broad range of capability areas, including conc

ANEE is an experimental dynamic inference wrapper for pretrained Transformer language models (currently GPT-2). Instead of always running all layers, ANEE exposes an energy_budget and performs early exit inside the model’s forward pass.

A helpful Chrome extension for WebGL development

Track and manage build artifacts from multiple programming languages.

The autonomous, self-improving AI agent. Single Rust binary. Every channel.

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Leave One Feature Out Importance

Graphback - Out of the box GraphQL server and client

This project is a curated directory of command line applications and utilities designed to enhance developer productivity and streamline technical workflows. It serves as a comprehensive index of open-source software, categorizing tools that assist with system administration, development automation, and personal task management. The repository distinguishes itself by providing a structured collection of terminal-based software that spans diverse functional domains. It includes resources for managing infrastructure and cloud resources, performing code maintenance, and customizing terminal envi

This project is a developer knowledge base and a curated library of programming code snippets. It serves as a multi-language coding reference that provides short technical articles and reusable code samples to help developers implement common programming patterns. The resource functions as a multi-language syntax reference, allowing for the comparison of logic and functionality across different programming environments. It focuses on programming pattern learning and coding skill improvement through a collection of optimized patterns and best practices. The platform includes capabilities for