Program implements a convolutional neural network for classifying images of numbers in the MNIST dataset as either even or odd using GPU framework.
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Updated
Dec 25, 2020 - Jupyter Notebook
Program implements a convolutional neural network for classifying images of numbers in the MNIST dataset as either even or odd using GPU framework.
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Sequential Convolutional Neural Network for handwritten digits recognition trained on MNIST dataset using keras API
A project from the AI_primer course at Vilnius university.
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A repository to show how Dropout in Keras can Prevent Overfitting
Used tensorflow's neural network model to predict whether or not a person pays back a loan on the basis of his historical data and personal details of 3.9 lakh people like interest rate, employment details, address, etc.
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Keras Deep Learning projects including Classifying Images for ImageNet data using CNNs, Transfer Learning and Hyperparameter Optimization
Dropout: A Simple Way to Prevent Neural Networks from Overfitting
Predicting Turbine Energy Yield (TEY) using ambient variables as features.
67% accuracy on test set of CIFAR-100 by CNN in Keras without transfer learning
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