Pytorch Tutorials Kr🇰🇷PyTorch에서 제공하는 튜토리얼의 한국어 번역을 위한 저장소입니다. (Translate PyTorch tutorials in Korean🇰🇷)
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Covid19Analyses about the COVID-19 virus
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PyomogalleryA collection of Pyomo examples
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Deeplearning keras2Modification of fast.ai deep learning course notebooks for usage with Keras 2 and Python 3.
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Project kojakTraining a Neural Network to Detect Gestures and Control Smart Home Devices with OpenCV in Python
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ReferReferring Expression Datasets API
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Nlp adversarial examplesImplementation code for the paper "Generating Natural Language Adversarial Examples"
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TestovoeHome assignments for data science positions
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VdeVariational Autoencoder for Dimensionality Reduction of Time-Series
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Ml Mooc NptelThis repository contains the Tutorials for the NPTEL MOOC on Machine Learning.
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Phonetic Similarity VectorsSource code to accompany my paper "Poetic sound similarity vectors using phonetic features"
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ForecastingTime Series Forecasting Best Practices & Examples
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Feature SelectorFeature selector is a tool for dimensionality reduction of machine learning datasets
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SlayerpytorchPyTorch implementation of SLAYER for training Spiking Neural Networks
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Transformers RuA list of pretrained Transformer models for the Russian language.
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D6tstackQuickly ingest messy CSV and XLS files. Export to clean pandas, SQL, parquet
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StereoconvnetStereo convolutional neural network for depth map prediction from stereo images
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Learning by associationThis repository contains code for the paper Learning by Association - A versatile semi-supervised training method for neural networks (CVPR 2017) and the follow-up work Associative Domain Adaptation (ICCV 2017).
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Deeplab v2基于v2版本的deeplab,使用VGG16模型,在VOC2012,Pascal-context,NYU-v2等多个数据集上进行训练
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Ml From ScratchAll the ML algorithms, ML models are coded from scratch by pure Python/Numpy with the Math under the hood. It works well on CPU.
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Ml Workspace🛠 All-in-one web-based IDE specialized for machine learning and data science.
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Machine Learning🌎 machine learning tutorials (mainly in Python3)
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Book nbsNotebooks for upcoming fastai book (draft / incomplete)
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Face DepixelizerFace Depixelizer based on "PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models" repository.
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PracticaldlA Practical Guide to Deep Learning with TensorFlow 2.0 and Keras materials for Frontend Masters course
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Ai MatrixTo make it easy to benchmark AI accelerators
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Covid 19 Eda TutorialThis tutorial's purpose is to introduce people to the [2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE](https://github.com/CSSEGISandData/COVID-19) and how to explore it using some foundational packages in the Scientific Python Data Science stack.
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Computer visionC/C++/Python based computer vision models using OpenPose, OpenCV, DLIB, Keras and Tensorflow libraries. Object Detection, Tracking, Face Recognition, Gesture, Emotion and Posture Recognition
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CpndetCorner Proposal Network for Anchor-free, Two-stage Object Detection
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Homework fall2020Assignments for Berkeley CS 285: Deep Reinforcement Learning (Fall 2020)
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Nyc TransportA Unified Database of NYC transport (subway, taxi/Uber, and citibike) data.
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Stock Price PredictorThis project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
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Math With PythonVarious math-related things in Python code
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Sphereface PlusSphereFace+ Implementation for <Learning towards Minimum Hyperspherical Energy> in NIPS'18.
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Spark With PythonFundamentals of Spark with Python (using PySpark), code examples
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ParcelsMain code for Parcels (Probably A Really Computationally Efficient Lagrangian Simulator)
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Time Series Forecasting Of Amazon Stock Prices Using Neural Networks Lstm And GanProject analyzes Amazon Stock data using Python. Feature Extraction is performed and ARIMA and Fourier series models are made. LSTM is used with multiple features to predict stock prices and then sentimental analysis is performed using news and reddit sentiments. GANs are used to predict stock data too where Amazon data is taken from an API as Generator and CNNs are used as discriminator.
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