67% accuracy on test set of CIFAR-100 by CNN in Keras without transfer learning
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Updated
Nov 15, 2021 - Jupyter Notebook
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.
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.
Job Prediction given job description and skills
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.
In this project, comparison of glasses and toothbrushes was done by using deep learning algorithm.
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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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.
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