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ElephasDistributed Deep learning with Keras & Spark
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Hep mlMachine Learning for High Energy Physics.
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Scarpet NnTools and libraries to run neural networks in Minecraft ⛏
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PytorchnlpbookCode and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://nlproc.info
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CryptonetsCryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.
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SmrtHandle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.
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Micro Racing🚗 🏎️ 🎮 online 3D multiplayer neural networks based racing game
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Merlin.jlDeep Learning for Julia
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EmlearnMachine Learning inference engine for Microcontrollers and Embedded devices
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EnnuiAn Elegant Neural Network User Interface to build drag-and-drop neural networks, train in the browser, visualize during training, and export to Python.
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HyperdensenetThis repository contains the code of HyperDenseNet, a hyper-densely connected CNN to segment medical images in multi-modal image scenarios.
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BackpropagandaA simple JavaScript neural network framework.
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FlowppCode for reproducing Flow ++ experiments
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DeepsmilesDeepSMILES - A variant of SMILES for use in machine-learning
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Ml Workspace🛠 All-in-one web-based IDE specialized for machine learning and data science.
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Wav2letterSpeech Recognition model based off of FAIR research paper built using Pytorch.
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NnpackAcceleration package for neural networks on multi-core CPUs
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Math And Ml NotesBooks, papers and links to latest research in ML/AI
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Pytorch 101 Tutorial SeriesPyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.
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Mit Deep LearningTutorials, assignments, and competitions for MIT Deep Learning related courses.
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Kaggle RsnaDeep Learning for Automatic Pneumonia Detection, RSNA challenge
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Uncertainty MetricsAn easy-to-use interface for measuring uncertainty and robustness.
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Kitnet PyKitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.
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Ai BlocksA powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!
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JosefA robot who learns how to draw
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