Topic: deeplearing Goto Github
Some thing interesting about deeplearing
Some thing interesting about deeplearing
deeplearing,Satellite images segmentation with Unet and Transfer learning
User: anassboussarhan
deeplearing,This repository contains a PyTorch implementation of an algorithm for artistic style transfer. The algorithm can be used to mix the content of an image with the style of another image. For example, here is a photograph of a door arch rendered in the style of a stained glass painting.
User: cuicaihao
deeplearing,A reinforcement learning agent that plays PacMan
User: damilojohn
deeplearing,Simple Line/Kakao-Papago Translation Bot.
User: hunkim
Home Page: http://pf.kakao.com/_Txmtuxl
deeplearing,Detection of disease type in tomato leaves using Alexnet
User: koksalkapucuoglu
deeplearing,MultiScale_FeatureFusion CNN model with keras_2020
User: maddy023
deeplearing,Time series forecasting (TSF) is the task of predicting future values of a given sequence using historical data. Recently, this task has attracted the attention of researchers in the area of machine learning to address the limitations of traditional forecasting methods, which are time-consuming and full of complexity. With the increasing availability of extensive amounts of historical data along with the need of performing accurate production forecasting, particularly a powerful forecasting technique infers the stochastic dependency between past and future values is highly needed. In this research, we applied machine learning approach capable to address the limitations of traditional forecasting approaches and show accurate predictions and showed comparison of different machine learning models. For evaluation purpose, a case study from the petroleum industry domain is carried out using the production data of an actual gas field of Bangladesh. Toward a fair evaluation, the performance of the models were evaluated by measuring the goodness of fit through the coefficient of determination (R2 ) and Root Mean Square Error (RMSE), Mean Squared Error (MSE) , Mean Absolute Error(MAE) and model Accuracy
User: salmansust
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