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Delta Lake is an open-source storage framework designed to support the construction of a Lakehouse architecture. It is compatible with multiple compute engines including Apache Spark, PrestoDB, Flink, Trino, and Hive, as well as associated APIs.
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DemoGPT is a tool that enables users to create agentic applications using prompts. It provides all components required for LLM agent development, including tools, prompts, frameworks, and models, in a single package.
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Desbordante is a high-performance open-source data profiler. It uses a variety of algorithms to discover different patterns in data and supports running data cleaning scenarios using these algorithms. The tool is available as a console version and an easy-to-use web application.
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Detecto is a Python package for building computer vision and object detection models with PyTorch. It supports inference on still images and videos, transfer learning on custom datasets, and serialization of models to files, and is distributed under an MIT license.
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Detectron2 is Facebook AI Research's next generation library providing detection and segmentation algorithms, succeeding Detectron and maskrcnn-benchmark. It supports computer vision research projects and production applications at Facebook and includes capabilities such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, ViTDet and MViTv2. Models can be exported to TorchScript or Caffe2 format for deployment.
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Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. It works with PyTorch and TensorFlow, offering a Python library, command line interface, and web UI for managing machine learning workflows.
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Detextify is a Python library that removes unwanted pseudo-text from images generated by generative AI models. It runs text detection on an image, masks the detected text boxes and in-paints the masked regions until the image is text-free, either locally or through existing APIs.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Basic proof of concept for genetic architecture search in Keras.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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DevOpsGPT is a multi-agent system for AI-driven software development. It combines large language models with DevOps tools to convert natural language requirements into working software, supporting any development language and extending existing code.
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Deep learning in Rust, with shape checked tensors and neural networks.
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Open-source project that supports AI agents, automated workflows, orchestration, or delegated tasks.
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Dify is an open-source LLM app development platform with a visual canvas for AI workflows and RAG pipelines, plus model management and observability. It can be deployed on cloud, VPC, or self-hosted, and integrates with proprietary and open-source LLMs.
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DIGITS, the Deep Learning GPU Training System, is a webapp for training deep learning models. The repository was archived by its owner on Jan 7, 2025 and is now read-only. NVIDIA states it is no longer adding features, fixing bugs, or supporting the software. Users can continue to use it if it meets their needs.
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Open-source project that applies AI to data analysis, extraction, visualization, or business intelligence.
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Frankensteinian amalgamation of notebooks, models and techniques for the generation of AI Art and Animations.
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Julia module for Distance evaluation.
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distilabel is a framework for synthetic data generation and AI feedback intended for engineers. It provides fast, reliable, and scalable pipelines based on verified research papers, supporting data synthesis for AI systems and on-the-fly feedback addition. The framework aims to improve AI output quality via enhanced data quality, give users control over their data and models, and boost efficiency through rapid iteration on research and large language models.
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Repository containing references and code for the book Distributed Machine Learning Patterns from Manning Publications by Yuan Tang. The book covers applying patterns to build scalable and reliable machine learning systems, constructing pipelines with data ingestion, distributed training and model serving, and automating tasks with Kubernetes, TensorFlow, Kubeflow and Argo Workflows.
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A Julia package for probability distributions and associated functions.
Archived, read-only GitHub repository of free resources for learning machine learning with Python and Jupyter Notebook, including notebooks, courses and other links. It was first posted in 2016 and was archived by the owner on Jun 27, 2022.
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A deep learning-based translation library between 50 languages, built with transformers.