Using ConvNet as feature extractor using nolearn and lasagne

Deep Learning models with vanilla & PyTorch implementations. Projects, Research, Theory and homeworks

Prostate lesion classification using Deep Convolutional Neural Networks

Architectures of convolutional neural networks for image classification in PyTorch

Final project for the course Human Data Analytics (UniPD)

Hack Submitted in HackInTheNorth4 at IIIT Allahabad, India.

Detailed custom implementations of Convolution operations in Pytorch for educational purposes.

The goal of this project is to build a robust traffic signs classifier by the magical powers of deep neural networks and the the dataset provided by the German Traffic Signs Dataset.

EL_3003-IA_et_Deep_Learning is an introduction to deep learning. The final project consists in comparing different types of classifiers such as CNN, KNN, SVM, on a face recognition problem.

Simple convolutional neural network (purely numpy) to classify the original MNIST dataset. My first project with a convnet. 🖼

Build CNN with theano

Q-learning Neural Network learning to steer a car and avoid obstacles. Uses ConvNet library.

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Learn basics of TensorFlow step by step

The MNIST dataset tackled by several machine learning models coded from scratch

Detection of autism through the machine learning and deep learning analysis of Magnetoencephalography scans.

Various keras deep learning models on colaboratory

Code for "Improving Stain Invariance of CNNs for Segmentation by Fusing Channel Attention and Domain-Adversarial Training"