Research Paper NotesNotes and Summaries on ML-related Research Papers (with optional implementations)
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FauxtographTools for using a variational auto-encoder for latent image encoding and generation.
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Kitti DatasetVisualising LIDAR data from KITTI dataset.
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PaddlehelixBio-Computing Platform featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集
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Text ClassificationText Classification through CNN, RNN & HAN using Keras
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Dl For ChatbotDeep Learning / NLP tutorial for Chatbot Developers
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Python AwesomeLearn Python, Easy to learn, Awesome
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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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Timeseries fastaifastai V2 implementation of Timeseries classification papers.
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OwnphotosSelf hosted alternative to Google Photos
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Malware DetectionMalware Detection and Classification Using Machine Learning
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HtmresearchExperimental algorithms. Unsupported.
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Edavizedaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab
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Rl Adventure 2PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
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WeightwatcherThe WeightWatcher tool for predicting the accuracy of Deep Neural Networks
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PaperboyA web frontend for scheduling Jupyter notebook reports
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Gwu data miningMaterials for GWU DNSC 6279 and DNSC 6290.
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Ipython NotebooksA collection of IPython notebooks covering various topics.
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CardioCardIO is a library for data science research of heart signals
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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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MelusineMelusine is a high-level library for emails classification and feature extraction "dédiée aux courriels français".
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TcdfTemporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
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NaviganNavigating the GAN Parameter Space for Semantic Image Editing
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MaterialsBonus materials, exercises, and example projects for our Python tutorials
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How To Read PytorchQuick, visual, principled introduction to pytorch code through five colab notebooks.
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Sklearn pycon2014Repository containing files for my PyCon 2014 scikit-learn tutorial.
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Python SonicProgramming Music with Python, Sonic Pi and Supercollider
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Vae ClusteringUnsupervised clustering with (Gaussian mixture) VAEs
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Stock market predictionThis is the code for "Stock Market Prediction" by Siraj Raval on Youtube
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Vqa demoVisual Question Answering Demo on pretrained model
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Stock PredictionStock price prediction with recurrent neural network. The data is from the Chinese stock.
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TutorialsAI-related tutorials. Access any of them for free → https://towardsai.net/editorial
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Scikit GeometryScientific Python Geometric Algorithms Library
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MirrorVisualisation tool for CNNs in pytorch
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Triplet AttentionOfficial PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]
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SecSeed, Expand, Constrain: Three Principles for Weakly-Supervised Image Segmentation
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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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