67% accuracy on test set of CIFAR-100 by CNN in Keras without transfer learning

A repository to show how Dropout in Keras can Prevent Overfitting

This is Collection of Regularization Deep learning techniques with code and paper

Building & Deploying Computer Vision Models

Understanding hyperparameters of neural network architectures using 3 cost functions, 3 activation functions, 2 regularizations and dropout.

Predicting Turbine Energy Yield (TEY) using ambient variables as features.

Dropout: A Simple Way to Prevent Neural Networks from Overfitting

Program implements a convolutional neural network for classifying images of numbers in the MNIST dataset as either even or odd using GPU framework.

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.

Job Prediction given job description and skills

Keras Deep Learning projects including Classifying Images for ImageNet data using CNNs, Transfer Learning and Hyperparameter Optimization

Cats vs dogs classification using deep learning. Data augmentation and convolutional neural networks.

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.

In this project, comparison of glasses and toothbrushes was done by using deep learning algorithm.

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Deep Neural Network Spam Email Classifier

A simple study on the use of Keras framework (with Tensorflow background) for a simple handwritten number image classification task with Deep Neural Networks.