Articles About Natural Language Processing

A tool to convert AWS EC2 instances back and forth between On-Demand

ec2-spot-converter This tool converts existing AWS EC2 instances back and forth between On-Demand and ‘persistent’ Spot billing models while preserving instance attributes (Launch configuration, Tags..), network attributes (existing Private IP addresses, Elastic IP), storage (Volumes), Elastic Inference accelerators, Elastic GPUs. Others features: Can also perform Spot-to-Spot and OnDemand-to-OnDemand conversions: Allow replacement of existing Spot instances with new “identical” ones to update the instance type and CPU options, Help to fix some Spot instance conditions (Ex: ‘IncorrectSpotRequestState Exception’), Allow Root Disk […]

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Halftone with Points And Lines

HalftonePAL This arranges points on an image for halftoning, using the circles themselves, dots at their centers, or lines connecting the circles. Features: Choose how to arrange the circles: Circle packing, quadtree, random dither, 1D and 2D error diffusion on square or hex grids. Choose what pattern to make from the circles: Show dots, circles, tilted lines, scan back-and-forth, connect the points with a Hilbert curve, make a greedy path between points, a greedy loop, a minimum spanning tree, a […]

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Focal Frequency Loss for Generative Models

focal-frequency-loss This repository will provide the official code for the following paper: Focal Frequency Loss for Generative ModelsLiming Jiang, Bo Dai, Wayne Wu and Chen Change LoyarXiv preprint, 2020. Abstract: Despite the remarkable success of generative models in creating photorealistic images using deep neural networks, gaps could still exist between the real and generated images, especially in the frequency domain. In this study, we find that narrowing the frequency domain gap can ameliorate the image synthesis quality further. To this […]

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Writing high-level code for parallel high-performance stencil computations

ParallelStencil.jl ParallelStencil empowers domain scientists to write architecture-agnostic high-level code for parallel high-performance stencil computations on GPUs and CPUs. Performance similar to CUDA C can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding CUDA.jl Array programming implementation; in absolute terms, it reached 70% of the theoretical upper performance […]

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Machine Learning and Deep Learning Courses

If you follow me on Twitter, you will know that I have been curating and sharing some of the most recent machine learning, natural language processing (NLP), and deep learning courses that have been publicly released. I have completed the majority of these courses and some I am currently reviewing. At the request of some people, I have decided to write this blog post so that it is easier to maintain and bookmark the complete collection of courses. Here they […]

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Python Client for TerminusDB

TerminusDB Client Python Python version of the TerminusDB client – for TerminusDB API and WOQLpy Requirements Installation TerminusDB Client can be downloaded form PyPI using pip:python -m pip install terminusdb-client This only includes the core Python Client (WOQLClient) and WOQLQuery. If you want to use woqlDataframe: python -m pip install terminusdb-client[dataframe] if you are installing form zsh you have to quote the argument like this: python -m pip install ‘terminusdb-client[dataframe]’ python -m pip install git+https://github.com/terminusdb/terminusdb-client-python.git Usage >>> from terminusdb_client import […]

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Detectron2 for Document Layout Analysis

Detectron2 This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Detectron2 implementation.PubLayNet is a very large dataset for document layout analysis (document segmentation). It can be used to trained semantic segmentation/Object detection models. NOTE Models are trained on a portion of the dataset (train-0.zip, train-1.zip, train-2.zip, train-3.zip) Trained on total 191,832 images Models are evaluated on dev.zip (~11,000 images) Backbone pretrained on COCO dataset is used but trained from scratch on PubLayNet dataset Trained […]

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Tools to Design or Visualize Architecture of Neural Network

Net2Vis: Net2Vis automatically generates abstract visualizations for convolutional neural networks from Keras code. visualkeras : Visualkeras is a Python package to help visualize Keras (either standalone or included in tensorflow) neural network architectures. It allows easy styling to fit most needs. As of now it supports layered style architecture generation which is great for CNNs (Convolutional Neural Networks) and a grap style architecture. import visualkeras model = … visualkeras.layered_view(model).show() # display using your system viewer visualkeras.layered_view(model, to_file=’output.png’) # write to […]

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BErt-like Neurophysiological Data Representation

BENDR BErt-like Neurophysiological Data Representation. This repository contains the source code for reproducing, or extending the BERT-like self-supervision pre-training for EEG data from the article: BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data To run these scripts, you will need to use the DN3 project. We will try to keep this updated so that it works with the latest DN3 release. If you are just looking for the BENDR model, and […]

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Official implementation of Monocular Quasi-Dense 3D Object Tracking

qd-3dt Monocular Quasi-Dense 3D Object Tracking (QD-3DT) is an online framework detects and tracks objects in 3D using quasi-dense object proposals from 2D images. Monocular Quasi-Dense 3D Object Tracking,Hou-Ning Hu, Yung-Hsu Yang, Tobias Fischer, Trevor Darrell, Fisher Yu, Min Sun,arXiv technical report (arXiv 2103.07351)Project Website (QD-3DT) @article{Hu2021QD3DT, author = {Hu, Hou-Ning and Yang, Yung-Hsu and Fischer, Tobias and Yu, Fisher and Darrell, Trevor and Sun, Min}, title = {Monocular Quasi-Dense 3D Object Tracking}, journal = {ArXiv:2103.07351}, year = {2021} } […]

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