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GitHub intanq semi supervised learning Semi supervised
Topics Intank Services Intanq Driving Quality and Intank Services Delivering Quality Server
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Intanq
INTANQ PTE LTD 200810651G Singapore Company
Implements a question answering system with several knowledge bases such as web scraped the most relevant website summarized and not summarized and user provided knowledge base Using a pretrain
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GitHub intanq Question Answering Intelligent System
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GitHub intanq Transfer Learning ResNet18 Implement
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Implements FFNN feed forward neural networks and CNN convolutional neural network to perform classification tasks on MNIST and SVHN datasets
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Question Answering Intelligent System app py at main intanq
Pandai is a learning app that helps students get better grades in school through game like quizzes tests exams notes videos and more
Implementation on PCA Autoencoder and Variational Autoencoder AI Postgrad Student intanq has 23 repositories available Follow their code on GitHub
intanq FFNN and CNN using MNIST and SVHN Datasets
INTANQ PTE LTD was incorporated on 30 May 2008 Friday as a Exempt Private Company Limited by Shares in Singapore The Company current operating status is struck off with registered address at THE CENTRAL The Company principal activity is in MANAGEMENT CONSULTANCY SERVICES GENERAL
Semi supervised learning on MNIST dataset Using pretrained layers trained using Autoencoder and Variational Autoencoder algos to perform multiclass classification intanq semi supervised learning
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Implements a question answering system with several knowledge bases such as web scraped the most relevant website summarized and not summarized and user provided knowledge base Using a pretrained model DistilBERT and Tesseract OCR to recognize handwritten questions
Transfer Learning using Resnet18 to classify images in OFFICE31 datasets There are 2 types of transfer learning that were performed which are Implement multiclass classification task to classify images by using pretrained model ResNet18 Transfer learning with feature extractor and finetuning are used
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