A project from the AI_primer course at Vilnius university.
-
Updated
Jan 19, 2024 - Jupyter Notebook
A project from the AI_primer course at Vilnius university.
Cats vs dogs classification using deep learning. Data augmentation and convolutional neural networks.
Dropout: A Simple Way to Prevent Neural Networks from Overfitting
Building & Deploying Computer Vision Models
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
A simple study on the use of Keras framework (with Tensorflow background) for a simple handwritten number image classification task with Deep Neural Networks.
A repository to show how Dropout in Keras can Prevent Overfitting
Program implements a convolutional neural network for classifying images of numbers in the MNIST dataset as either even or odd using GPU framework.
Understanding hyperparameters of neural network architectures using 3 cost functions, 3 activation functions, 2 regularizations and dropout.
Job Prediction given job description and skills
rate customer reviews
Sequential Convolutional Neural Network for handwritten digits recognition trained on MNIST dataset using keras API
Deep Neural Network Spam Email Classifier
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.
This is Collection of Regularization Deep learning techniques with code and paper
Keras Deep Learning projects including Classifying Images for ImageNet data using CNNs, Transfer Learning and Hyperparameter Optimization
In this project, comparison of glasses and toothbrushes was done by using deep learning algorithm.
Add a description, image, and links to the dropout-keras topic page so that developers can more easily learn about it.
To associate your repository with the dropout-keras topic, visit your repo's landing page and select "manage topics."