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An optimization library for Torch. SGD, Adagrad, Conjugate-Gradient, LBFGS, RProp and more.
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Google TPU optimizations for transformers models.
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Python-based meta-heuristic optimization techniques.
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Google's Operations Research 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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Passive OSINT reconnaissance framework in Rust: subdomains, DNS, ASN, certificate transparency history, GitHub dorking, tech fingerprinting, emails an
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Machine Learning Framework from Industrial Practice.
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Resource scheduling and cluster management for AI.
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Parris, the automated infrastructure setup tool for machine learning algorithms.
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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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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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A complete object-oriented environment for machine learning in Matlab.
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Enables single machine or distributed training and evaluation of deep learning models.
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A Julia framework for probabilistic graphical models.
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Python library for working with Probabilistic Graphical Models.
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GitHub OSINT collection with tools, links, and resources for online investigation workflows.
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Retrieval Augmented Generation (RAG) framework and context engine powered by Pinecone.
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A JavaScript application framework for machine learning and its engineering.
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A better version of Jieba, developed by Peking University.
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Production-Ready LLM Agent SDK for Every Developer.
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Python Machine Learning Pentesting Toolbox for Adversarial Attacks. Works with LLMs, DNNs, and other machine learning algorithms.
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Use AutoML to do model compression.
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A platform for reproducible and scalable machine learning and deep learning on kubernetes.
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Multilingual text (NLP) processing toolkit.