Search Results for "cuda machine learning" - Page 2
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Showing 35 open source projects for "cuda machine learning"
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Image Super-Resolution (ISR)
Super-scale your images and run experiments with Residual Dense
The goal of this project is to upscale and improve the quality of low-resolution images. This project contains Keras implementations of different Residual Dense Networks for Single Image Super-Resolution (ISR) as well as scripts to train these networks using content and adversarial loss components. Docker scripts and Google Colab notebooks are available to carry training and prediction. Also, we provide scripts to facilitate training on the cloud with AWS and Nvidia-docker with only a few... -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out... -
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YouTube-8M
Starter code for working with the YouTube-8M dataset
youtube-8m is Google’s open source starter code and reference implementation for training and evaluating machine learning models on the YouTube-8M dataset, one of the largest video understanding datasets publicly released. The repository provides a complete pipeline for video-level and frame-level modeling using TensorFlow, including data reading, model training, evaluation, and inference. It was developed to support the YouTube-8M Video Understanding Challenge (hosted on Kaggle and featured at ICCV 2019), enabling researchers and practitioners to benchmark video classification models on large-scale datasets with over millions of labeled videos. ... -
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Training Image Operators from Samples
Tools to train Image Operators automatically from a set of samples.
TRIOS - Training Image Operators from Samples is a set of tools to bring Image Processing closer to scientists in general. It is capable of estimating an operator between two images using only pairs of samples that contain an input image and the desired output. The operator is saved to a file and can be applied to any image. -
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pyELib
A free open source system to create and manage collections of eBooks
...Unlike other eBooks management softwares, pyELib doesn't need the user to input neither titles nor ISBNs, since it automatically analyzes the files and searches for details on the internet. Dupes and different editions are properly handled. Each book is then automatically associated to one or more category (through machine learning) and, if desired, renamed. The library is stored in a MySQL database and comes with an interface for easier management. -
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MyNook
A machine learning system for supervised document classification
An open source system for supervised document classification based on statistical machine learning techniques. On the contrary of the state of art classification techniques, MyNook just requires the title of the document, not the content itself. -
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Pronac MediaMonkey Extension
Recommends music based upon your current taste.
...Play the first song from the Now Playing list, it'll recommend you next songs from the same list. NOTE: MAKE SURE THAT SONG SHUFFLE IS TURNED OFF WHILE USING PRONAC. Based upon K-Nearest Neighbor Machine Learning Algorithm, K-Fold Cross Validation and EchoNest for audio features. -
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The Python Computer Vision Framework is an opened project deisgned for all those interested in computer vision. It aims at making computer vision more easy and structured and matlab-free. It may also be used for other artistic and scientific areas.
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