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Pixel level land classificationTutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
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SoltStreaming over lightweight data transformations
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Multiclass Semantic Segmentation CamvidTensorflow 2 implementation of complete pipeline for multiclass image semantic segmentation using UNet, SegNet and FCN32 architectures on Cambridge-driving Labeled Video Database (CamVid) dataset.
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Pytorch UnetSimple PyTorch implementations of U-Net/FullyConvNet (FCN) for image segmentation
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LovaszsoftmaxCode for the Lovász-Softmax loss (CVPR 2018)
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Wiki DetoxSee https://meta.wikimedia.org/wiki/Research:Modeling_Talk_Page_Abuse
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SynapseSamples for Azure Synapse Analytics
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PytextrankPython implementation of TextRank for phrase extraction and summarization of text documents
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Kaggle challengeThis is the code for "Kaggle Challenge LIVE" By Siraj Raval on Youtube
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Nestedtensor[Prototype] Tools for the concurrent manipulation of variably sized Tensors.
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Vae TensorflowA Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).
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Pandaspandas cheetsheet
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Perfil PoliticoA platform for profiling public figures in Brazilian politics
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Planet Amazon DeforestationThe open source repository for the Kaggle Amazon forest devastation competition https://www.kaggle.com/c/planet-understanding-the-amazon-from-space
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Bayes By BackpropPyTorch implementation of "Weight Uncertainty in Neural Networks"
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ChromaganOfficial Implementation of ChromaGAN: An Adversarial Approach for Picture Colorization
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Dstl unetDstl Satellite Imagery Feature Detection
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Reinforcementlearning AtarigamePytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games
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Linear Attention Recurrent Neural NetworkA recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)
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Teach Me Quantum⚛ 10 week Practical Course on Quantum Information Science and Quantum Computing - with Qiskit and IBMQX
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NotebooksCurated Notebooks from STScI
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Abstractive Text SummarizationPyTorch implementation/experiments on Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond paper.
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ObjectdetectionSome experiments with object detection in PyTorch
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Midi DatasetCode for creating a dataset of MIDI ground truth
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