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PaperboyA web frontend for scheduling Jupyter notebook reports
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Vqa demoVisual Question Answering Demo on pretrained model
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Scikit GeometryScientific Python Geometric Algorithms Library
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LfortranOfficial mirror of https://gitlab.com/lfortran/lfortran. Please submit pull requests (PR) there. Any PR sent here will be closed automatically.
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Ipython NotebooksA collection of IPython notebooks covering various topics.
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MirrorVisualisation tool for CNNs in pytorch
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TutorialTutorial covering Open Source tools for Source Separation.
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Set transformerPytorch implementation of set transformer
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Interpret TextA library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.
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MaterialsBonus materials, exercises, and example projects for our Python tutorials
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Zoom Learn Zoomcomputational zoom from raw sensor data
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Amazing Feature EngineeringFeature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
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OwnphotosSelf hosted alternative to Google Photos
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Lrp toolboxThe LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Python. The Toolbox realizes LRP functionality for the Caffe Deep Learning Framework as an extension of Caffe source code published in 10/2015.
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SecSeed, Expand, Constrain: Three Principles for Weakly-Supervised Image Segmentation
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Text summarization with tensorflowImplementation of a seq2seq model for summarization of textual data. Demonstrated on amazon reviews, github issues and news articles.
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HtmresearchExperimental algorithms. Unsupported.
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Timeseries fastaifastai V2 implementation of Timeseries classification papers.
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Source separationDeep learning based speech source separation using Pytorch
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Practical 1Oxford Deep NLP 2017 course - Practical 1: word2vec
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18s09618.S096 three-week course at MIT
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