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A curated list of generative deep learning tools, works, models, etc. for artistic uses, by @filipecalegario.
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A library for developing and comparing reinforcement learning algorithms (successor of [gym])(https://github.com/openai/gym).
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Distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Implementation of image to image (pix2pix) translation from the paper by isola et al.[DEEP LEARNING].
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Koç University Deep Learning Framework.
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Deep learning framework written in Kotlin.
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Lightly is a computer vision framework for self-supervised learning.
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A Julia package for manifold learning and nonlinear dimensionality reduction.
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Application-oriented deep reinforcement learning framework addressing real-world decision problems.
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MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto-differentiation.
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Flexible Deep Learning Framework in Julia.
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An open source robotics benchmark for meta- and multi-task reinforcement learning.
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Neural networks (boltzmann machines, feed-forward and recurrent nets), Gaussian Processes.
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MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios.
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500+ ML/AI interview Q&A with runnable code — covers ML fundamentals, deep learning, NLP, PyTorch, scikit-learn pipelines, and system design.
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A modular active learning framework for Python, built on top of scikit-learn.
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List of molecular design using Generative AI and Deep Learning.
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Support Vector Machine for Node.js.
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An open-source cross-platform performance library for deep learning applications.
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OneFlow is a performance-centered and open-source deep learning framework.
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An ONNX (Open Neural Network eXchange) API and backend for typeful, functional deep learning in Scala (3).
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A Python library for secure and private Deep Learning built on PyTorch and TensorFlow.
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A Modular Framework for Multi-Modal Tabular Learning.
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Deep learning framework to train, deploy, and ship AI products Lightning fast.