general-adversarial-network

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

Presentation material for my talk at Pycon DE 2023: Intro on synthetic tabular data including synthetic data generation, evaluation metrics and common problems of synthetic data generation projects.

Automating detecting tigers 🐅 in the wild 🌳 by handling illumination issues 💡 with the help of EnlightenGAN 🏞️

DCGAN implementation in keras on CIFAR10 dataset

Pytorch implementation of Generative Adversarial Networks (GAN) for MNIST and EMNIST datasets

Contains implementation of a GAN to generate human faces.

A PyTorch comparison of GAN and CNN architectures for upscaling heavily degraded QR codes back to scannable quality.

Generative Adversarial Networks for CIFAR-10 dataset written as part of my MSc in Data Science degree.

A proof of concept in Detecting Deceptive Deepfake Media Using Generative Adversarial Networks (GAN))

Generate faces using General Adversarial networks

Attempt to build a GAN based data repeater to enable our team to generate more data with "statistically adequate" fake data.

Defined and trained a DCGAN on a dataset of faces. The Goal of this project is to generate new images of faces that look as realistic as possible.

Notebooks completed to learn various Deep Learning topics during Inspirit AI's Deep Dives: Designing Deep Learning Systems program(500+ lines)

A GAN that sythesizes new faces alike faces from celebA dataset

Generation and Prediction of Images Using KERAS

Face generator

Generating fake images using Deep Convolutional GANs (DCGAN)

Chess game including state-of-the-art GUI, lichess.org game selection interface and review mechanic and a simple computer opponent to play against.