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Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone.
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Python library for working with Probabilistic Graphical Models.
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A Julia framework for probabilistic graphical models.
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Enables single machine or distributed training and evaluation of deep learning models.
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A complete object-oriented environment for machine learning in Matlab.
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This package contains the matlab implementation of the algorithms described in the book Pattern Recognition and Machine Learning by C. Bishop.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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A web mining module for the Python programming language. It has tools for natural language processing, machine learning, among others.
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Parris, the automated infrastructure setup tool for machine learning algorithms.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Resource scheduling and cluster management for AI.
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Machine Learning Framework from Industrial Practice.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
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Lambda Architecture Framework using Apache Spark and Apache Kafka with a specialization for real-time large-scale machine learning.
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Python-based meta-heuristic optimization techniques.
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Google TPU optimizations for transformers models.
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An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
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Jan - Run LLMs like Mistral or Llama2 locally and offline on your computer, or connect to remote AI APIs.
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Gitingest - Turn any Git repository into a simple text digest of its codebase so it can be fed into any LLM.
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A real-time multi-person keypoint detection library for body, face, hands, and foot estimation.
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A PyTorch-based framework to train and validate the models producing high-quality embeddings.
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Open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease.
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Open-source project that provides machine-learning models, research, training resources, or evaluation tools.