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Published directory entries matching your search.
agenttrace is a local-first terminal TUI and report generator for AI coding-agent session history. It reads logs from several coding agents and produces reports on cost, tokens, time, and slow-run diagnosis. Prompts, code, and logs stay on the local machine.
This is a Scaler blog category page collecting articles on artificial intelligence and machine learning. Posts listed include MLOps projects, becoming an AI research scientist, model drift detection and monitoring, and retrieval-augmented generation evaluation metrics. The page also links to categories such as software development and data science, and offers career counselling.
Amadeus Code provides music AI infrastructure spanning rights-cleared training data, audio supply and royalty management. Its products include MusicTGA for MIDI songwriting ideas, FUJIYAMA AI SOUND for music and sound materials, and Evoke Music, a royalty-free library. CONNECT is a royalty management platform for copyrights and master rights in Japan.
Arize Phoenix is an AI observability and evaluation tool built by Arize AI and the open-source community on OpenTelemetry and OpenInference. It provides tracing for debugging individual runs, evaluations to score output quality, a prompt playground, and datasets and experiments for comparing changes on the same inputs.
BayesPy is an open-source Python library that provides tools for performing Bayesian inference. It is hosted as a public repository on GitHub where users can access the code and contribute to its development.
Beam provides a bare-metal cloud for agents, with persistent forkable microVMs that boot in seconds and can be paused, resumed, network-isolated and GPU-accelerated. Virtual machines are billed per second while running, with no compute charges while stopped. The platform also offers serverless GPU tasks, sandboxes and on-demand GPU machines.
An open-source LLM gateway with routing, load balancing, guardrails, and observability for 1000+ models. opensource.
BurnRate is an AI usage analytics tool that tracks costs, tokens and usage patterns across AI coding providers. It connects OpenAI and Anthropic reporting accounts for provider-reported spend and offers a local CLI for session-level detail. Cloud workspaces come in Free, Pro at $12/month and Team at $29/seat/month plans.
ByteHub is an open-source tool designed to simplify the creation and management of feature stores. It is maintained as a public repository on GitHub under the bytehub-ai organization, with documentation and tutorials available for users.
Helps teams build, deploy, observe or operate machine-learning systems.
CHICKEN is a compiler for the Scheme programming language that produces portable and efficient C. It supports the R5RS and R7RS standards and many extensions, runs on Linux, OS X, Windows, and many Unix flavours, and is distributed free under the BSD License. Libraries and extensions are available at Eggs Unlimited.
CML, or Continuous Machine Learning, is an open-source CLI tool for implementing CI/CD with a focus on MLOps. It is used to automate development workflows, including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets. It can generate a visual report with results and metrics automatically on every pull request, using GitLab, GitHub, or Bitbucket.
Cortex Memory is a production-ready cognitive foundation for autonomous systems such as Embodied-AI and OpenClaw. It provides memory management functionality including extraction, search, and automated optimization, and includes SKILL, CLI, API, MCP, and an insights dashboard out-of-the-box.
Fast inference engine for Transformer models in C++.
Curated list of awesome vector search framework/engine, library, cloud service and research papers to vector similarity search.
Deepchecks is an open-source project for validating machine learning models and data from research to production. It includes built-in and custom checks and suites for tabular, NLP and CV validation, CI and testing management, and monitoring of deployed models. Installation is via pip.
DeepSpeed is a deep learning optimization library intended to make distributed training easy, efficient and effective. It offers system innovations including ZeRO, 3D-Parallelism, DeepSpeed-MoE and ZeRO-Infinity, and has been integrated with several open-source deep learning frameworks.
MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.
Eden AI offers a unified API for accessing large language models and specialist AI models, including OCR, speech, translation and vision. It standardizes requests, responses, authentication, billing and monitoring across providers, and supports routing requests by cost, performance and region.
Edge Impulse is an MLOps platform for edge AI and physical AI. It provides native MLOps workflows covering end-to-end pipelines, security, versioning and model monitoring, and is used to develop, deploy and manage AI solutions at scale across the edge hardware ecosystem. A Developer plan is offered at $0 per month.
Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for experimentation and research with probabilistic models, from hierarchical models on small data sets to deep probabilistic models on large data sets. It fuses Bayesian statistics and machine learning, deep learning, and probabilistic programming, and is built on TensorFlow.
Epsilla is a high-performance vector database hosted on GitHub under the epsilla-cloud organization. It leverages parallel graph computing for its operations, and offers an experimental option to use it as a Python library without requiring a Docker image, alongside Epsilla Cloud as a deployment option.
Evidently is an open-source observability framework for machine learning and large language models, hosted on GitHub under the evidentlyai organization. It enables users to evaluate, test, and monitor AI-powered systems and data pipelines, with support for use cases ranging from tabular data processing to generative AI, and includes more than 100 built-in metrics.
Faiss is a library for efficient similarity search and clustering of dense vectors, containing algorithms that search sets of vectors of any size. It is written in C++ with complete wrappers for Python/numpy, with some algorithms implemented on the GPU, and is developed primarily at Meta's Fundamental AI Research group.
