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Provides a comprehensive set of computer-vision algorithms and image/video processing utilities with multi-language bindings (C++, Python, Java), contrib modules, and community docs/forums — suitable for prototyping, production pipelines, and real-time applications.
Cross-platform API client for debugging, designing, testing and mocking GraphQL, REST, WebSockets, SSE and gRPC. Provides selectable storage backends (Local Vault, Git Sync, Cloud Sync with optional E2EE), a native OpenAPI editor, built-in test suites and a plugin ecosystem — useful for reproducible API development and pre-production validation.
Provides a NumPy/SciPy-compatible GPU array library for Python, enabling existing NumPy/SciPy numerical code to run on NVIDIA CUDA and AMD ROCm with minimal changes. Exposes low-level CUDA features (RawKernels, Streams) and offers prebuilt binaries for multiple CUDA/ROCm versions.
Sequence modeling toolkit for training custom models for translation, summarization, and language modeling. Reference implementation behind RoBERTa, BART, mBART, XLM-R, and wav2vec 2.0, with multi-GPU and mixed-precision training.
Expresses data quality checks as reusable, declarative "expectations" and auto-generates human-readable validation reports and docs; integrates with Python data stacks to enforce and monitor data reliability in ML and analytics pipelines.
Provides 150+ executed Jupyter notebooks and code that reproduce the book 'Machine Learning for Algorithmic Trading (2nd ed.)' — covers feature engineering, alternative-data signal extraction, backtesting, NLP, deep learning and reinforcement learning for trading; best for quant researchers and practitioners.
Brings classic computer vision into PyTorch as differentiable, GPU-accelerated tensor operators — filters, geometric transforms, feature matching, camera calibration — so each step lives inside autograd and trains end-to-end with neural networks.
Consolidates customer conversations from website chat, email, social and messaging channels into a single support inbox with self-hosting and Docker/one-click deployment options. Includes an optional AI agent (Captain) for automated replies, multilingual translation, and integrations.
Provides a hosted or self-hosted Postgres platform that exposes database, auth, realtime subscriptions, file storage, serverless functions, and auto-generated REST/GraphQL APIs. Includes an AI & vector/embeddings toolkit and modular client libraries for building web, mobile and AI applications without stitching multiple vendors.
Typed Python client for the OpenAI REST API that offers synchronous and asynchronous clients, typed request/response models, streaming and Realtime support, webhook verification, and integrations for Azure and Amazon Bedrock—built for production integrations and automation.