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3d-semantic-segmentation

Semantic Segmentation with Transformers on 3D Medical Images

3dify

Constructing 3D models out of 2D images

alexnet-pytorch

autoencoders

Learning all about autoencoders

brain-tumor-segmentation

Segmenting tumors using attention mechanism and ResNet based model in brain MRI scans from the BRaTs 2020 dataset.

clip-implementation

convnets-pytorch

covidclassification

ddpm-pokemon-sd

diffusion-ddpm-fashionmnist

diffusionmodel

Implementation of the basic diffusion model paper from scratch using PyTorch.

feedforward-nn-pytorch

Testing neural networks using Pytorch. Data taken from MNIST Database

gan-pytorch

gans-implementation

Implementation of GANs (2014) research paper

genetic-handwritten-digits

latent-diffusion

High-Resolution Image Synthesis with Latent Diffusion Models

lenet-5-pytorch

linear-regression-pytorch

Simple implementation of Linear Regression

nerfies.github.io

openai-assistants-template

Build and deploy AI-driven assistants with our OpenAI Assistants Template. This tutorial provides a hands-on approach to using OpenAI's Assistant API, complete with code modules, interactive Jupyter Notebook examples, and best practices to get you started on creating intelligent conversational agents.

papers-in-100-lines-of-code

Implementation of papers in 100 lines of code.

pix2pixpatch

playing-with-opencv

pytorch-mnist-celeba-cgan-cdcgan

Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset

pytorch-mnist-cvae

pytorch-mnist-vae

q-crusaders

simclr-urbansound8k

Explore advanced audio classification with SimCLR-UrbanSound8K. This repository applies SimCLR for urban sound categorization using the UrbanSound8K dataset, demonstrating state-of-the-art techniques in deep learning and audio analysis

splitwisegptvision

SplitwiseGPT Vision: Streamline bill splitting with AI-driven image processing and OCR. This innovative web app uses Pytesseract, GPT-4 Vision, and the Splitwise API to simplify group expense management. Upload bill images, auto-extract details, and seamlessly integrate expenses into Splitwise groups. Ideal for easy and accurate financial tracking

stable-dffusion-finetuning-flowers

A tutorial that guides users through the process of fine-tuning a stable diffusion model using HuggingFace's diffusers library. The tutorial includes advice on suitable hardware requirements, data preparation using the BLIP Flowers Dataset and a Python notebook, and detailed instructions for fine-tuning the model.