pygpu | pypi | Package Usage | Ecosyste.ms: Repos

bing-zhao/grab-aiforsea-safety

Submission to Grab AI for SEA Challenge (Safety)

==0.7.6 srcs/requirements.txt

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tesaho/vehicle_tracking

Stanford CS230 Deep Learning final project using YOLOv3 for vehicle detection

==0.7.6 requirements.txt

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MalteToetzke/deeplearning-for-automatic-music-transcription

Adversarial Training for Noise Robustness in Automatic Music Transcription

==0.7.6 ProjectFolder/Code/requirements.txt

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georgeblu1/Logia

Web application for performing end-to-end full-page handwriting recognition using the Apache MXNet deep learning frameworks on the IAM Dataset.

==0.7.6 requirements.txt

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arshjat/Attendance-Management-System

==0.7.6 requirements.txt

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anmol1270/insy

==0.7.6 Documents/insycon/10secondppt/updated-master/requirements.txt
==0.7.6 Documents/insycon/ff/requirements.txt

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ehsanasgari/DeepPrime2Sec

==0.7.6 installations/requirements.txt

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yangmingwanli/InspectAI

General Purpose Defect Inspection Tool

==0.7.6 requirements.txt

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anmol1270/10secppt

==0.7.6 Documents/insycon/10secondppt/updated-master/requirements.txt

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swathireddyp78/satellite_pose_estimation

==0.7.6 requirements.txt

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9lash/spotting_gunshots

Deep learning approach to classify gunshot over noisy audio

==0.7.6 requirements.txt

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MDSYN2019/PythonMDScripts

Folder containing the analysis code in C++/Python in MARTINI or SDK

==0.7.6 MD/MembraneLook/requirements.txt

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newjan/Vision-Based-Gesture-Recognition-and-Control

PCNavigation Using Hand Gestures

==0.7.6 requirements.txt

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Demian-KOR/Adv_Fin_ML_Exercises

==0.7.6 requirements.txt

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peterschnatz/BritePrice

==0.7.6 requirements.txt

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darkdefender228/detect_rectangle

==0.7.6 requirements.txt

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keegan8912/hack

Hackathon participation files

==0.7.6 requirements.txt

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RaymondDashWu/style-transfer-app

A deployed Flask version of Vince Marron's excellent style transfer work https://github.com/VinceMarron/style_transfer

==0.7.6 requirements2.txt

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kevsestrella/ObjectDetectionForAutonomousDriving

Object Detection For Autonomous Driving

==0.7.6 requirements.txt

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vtoliveira/evoman-artificial-intelligence

This repository presents an intelligent agent trained using neuroevolution techniques to play the evoman game.

==0.7.6 requirements.txt

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ibrica/Smotra2019

College fair demo app

==0.7.6 requirements.txt

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ChristopheBunn/Udacity-Data-Scientist-Nanodegree

Udacity Data Scientist Nanodegree - Christophe Bunn

==0.7.5 Jupyter Notebooks/8 - Software Engineering/5_deployment/bunnapp/requirements.txt

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rohit-malik/ComStory

==0.7.6 emotion_prediction2/fer2013/requirements.txt

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caikitlearn/stephen-ai-smith

stephen-ai-smith

==0.7.6 requirements.txt

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tharuka95/secura_global_backend

==0.7.6 requirements.txt

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swhan0329/Machine-Learning-for-Text-Mining

2019 IITP AI program, CMU Machine Learning for Text Mining 2019 FALL(11-441/641/741)

==0.7.6 hw2/src/requirements.txt

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allanfeitosa/VanHackton-BioConsious

==0.7.6 requirements.txt

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richellaod/DataRepresenationProject2019

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MarionMcG/dataRepresentation_bigProject

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oumaima1234/Django-MBD-Ecommerce

==0.7.6 requirements.txt

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marcusdaly/style

An exploration of deep multi-domain style transfer for natural language processing.

==0.7.5 requirements.txt

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rokuyon/make10_project

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ynnck/Reroot-website

==0.7.6 requirements.txt

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ShubhamOjha/dogclassifier-web-backend

==0.7.6 requirements.txt

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clementcome/BayesianSDE

Modelling of Bayesian Stochastic Differential Equations for the course of Bayesian Statistics at Politecnico di Milano.

==0.7.6 requirements.txt

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sayankotor/cqas

Comparative question answering system based on CAM

==0.7.6 requirements.txt

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ryosism/tripletloss_pytorch

==0.7.6 requirements.txt

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YBrady/dataRepProj

Data Representation Project

==0.7.6 requirements.txt

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guardiaum/BERT-SIDE

==0.7.6 requirements.txt

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saschahsp/guides_workshops

==0.7.6 DATASCIENCE/MODELS/ds-requirements.txt

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This project explores multi-domain style transfer for nat-ural language processing, based on recent research for im-ages. The goal is to encode styled text content to an objec-tive latent distribution which can be decoded into differentstyles. To accomplish this we train LSTM-based autoen-coders for each domain; these are trained using a common discriminator to elicit a shared latent distribution.

==0.7.5 requirements.txt

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akamojo/AnimeStyleTransfer

A project for Deep Neural Networks course

==0.7.6 requirements.txt

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xinaodan/leaf-classifier

==0.7.6 requirements.txt

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BlackPepperAPI/Cadene.pytorch

Cascaded (Task-oriented) Video denoiser which cascade video denoiser with High-level vision module, e.g. video actionnet or video segmentation.

==0.7.6 requirements.txt

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Gateway2745/Aerial-Object-Detection-Visualization

Bounding Box Visualization Scripts

==0.7.6 requirements.txt

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classic-panda/machine_learning

==0.7.6 requirements.txt

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kunalj101/LTFS-Data-Science-FinHack2

==0.7.6 Rank_3_Zishan/requirements.txt

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Sandy1811/deployment-of-deeplearning-model

==0.7.6 requirements_old.txt

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ChaudhariShubham/Review-Scrapper

==0.7.6 requirements.txt

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AxelStbl/jokes_score

==0.7.6 requirements.txt

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lewisbails/nfl-project

NFL Observational Study

==0.7.6 requirements.txt

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MaulyGabriel/balance

Qr Code Reader

==0.7.6 requirements.txt

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team-botnets/nec_ai_hack

This repository contains the source code for the NEC AI hackathon 2020.

==0.7.6 license_plate/requirements.txt

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mc28-cc/sanushi

Sanushi coding task

==0.7.6 requirements.txt

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vkreddy19/text-extraction-from-images

==0.7.6 text_extraction/requirements.txt

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woodfin8/big-data-challenge

==0.7.6 requirements.txt

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sidhartha-roy/federated-credit-default

This project uses federated ML to calculate the credit default risk of customers from two different databases.

==0.7.6 requirements.txt

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klebermagno/covid-19br

Simulação da curva

==0.7.6 data/requirements.txt

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zh3389/text_class

通用文本分类 -> keras+tensorflow -> 部署文件pb tf-serving docker-serving -> 客户端 client.py

==0.7.6 requirements.txt

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isshamie/covid19-S-Protein

==0.7.6 requirements.txt

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Ravi-Maurya/Intracranial_Hemorrhage_Segmentation

Segmentation with deep convolution networks

==0.7.6 requirements.txt

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greglee1905/Phragmites_australis_Classification

Classification of the invasive plant Phragmites australis in the Howard Slough Waterfowl Management Area.

==0.7.6 requirements.txt

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gayong-song/vDjBook

==0.7.6 requirements.txt

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IMIshitaMalhotra/NEO

NEO Database Udacity Project

==0.7.6 requirements.txt

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Skipper609/pothole_backend

This contains all the backend and the model

==0.7.6 backend-heroku/requirements.txt

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Rajathbharadwaj/NFS-Payback-AI

AI play NFS Payback

==0.7.6 requirements.txt

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ashish199820/atm-seurity

==0.7.6 requirements.txt

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Chase2816/textclass

==0.7.6 requirements.txt

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agilebeat-inc/maprover--utility-model-farming

the process of modeling and AWS lambda deployment

==0.7.6 requirements.txt

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lozanocelia/trading

==0.7.6 requirements.txt

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brandonjurado/Covid19Hack

Earth Hack 2020

==0.7.6 StatsModelsFW/requirements.txt

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benlevyx/modelling-infectious-disease

Modelling the spread of COVID-19 and the seasonal flu

==0.7.6 notebooks/streamlit-app/requirements.txt

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anmol1810rs/NEURAL_NETWORKS

==0.7.6 requirements.txt

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ssajous/europa-cycloids

==0.7.6 requirements.txt

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davidjurado/dog-breed-classification

CNN dog breed classifier in pytorch

==0.7.6 requirements.txt

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PRATIKSHIRBHATE/air_passenger_time_series

==0.7.6 requirements.txt

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limbachia/data-science

My springboard coursework

==0.7.6 SWE-for-DS/productionizing/titanic_datascience/requirement.txt

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saschahsp/ocids

==0.7.6 affinity_card/model/ds-requirements.txt
==0.7.6 model_rf/ds-requirements.txt
==0.7.6 model_rf/my_rf_model/ds-requirements.txt
==0.7.6 model_rf/my_rf_model/wo_pipeline/ds-requirements.txt
==0.7.6 model_rf/my_rf_model_automl/ds-requirements.txt
==0.7.6 models/model_deply_example/ds-requirements.txt
==0.7.6 models/1/ds-requirements.txt
==0.7.6 models/1/lgbm/ds-requirements.txt
==0.7.6 models/current/ds-requirements.txt
==0.7.6 models/lgbm/ds-requirements.txt

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hamaadshah/autoencoders_tensorflow

Automatic feature engineering using deep learning and Bayesian inference using TensorFlow.

==0.7.6 requirements.txt

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CookeRichard94/Emerging-Technologies-2019

Application for recognizing user inputs in range 0-9 using the MNIST dataset. Developed using Keras neural network, Flask server and JavaScript

==0.7.6 requirements.txt

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hamaadshah/market_risk_gan_tensorflow

Using Bidirectional Generative Adversarial Networks to estimate Value-at-Risk for Market Risk Management using TensorFlow.

==0.7.6 requirements.txt

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rfflpllcn/ml

playing with machine learning algos and data

==0.7.6 examples/advances-in-financial-ml-notes-2/requirements.txt

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akki6843/data_dive

This repo is for refreshing Machine learning based algos and methods.

==0.7.6 .ipynb_checkpoints/requirements-checkpoint.txt
==0.7.6 requirements.txt

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wyattowalsh/NBA-attendance-prediction

Attendance prediction tool for NBA games using machine learning. Full pipeline implemented in Python from data ingestion to prediction. Attained mean absolute error of around 800 people (about 5% capacity) on test set.