Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)

PyTorch implementations of Generative Adversarial Networks.

Release for Improved Denoising Diffusion Probabilistic Models

In this project we used a k-nearest neighbors algorithm (KNN) to recommend a book based on your previous book prefrecnces.

In this Project we will train our RNN model by giving it different tweets and then predict the sentiments of the tweets.

In this project we are using LSTM to classify texts as spam or ham.

In this project we will predict the cost required for a patient depending on his/her health conditions.

In this project we will classify Dog and Cat images using Convolution Neural Network (CNN)

I am an Artificial Intelligence Engineer with expertise in Machine Learning and Computer Vision.

Linear Regression using Matlab on a Kaggle dataset.

Using vision-language models to decode natural image perception from non-invasive brain recordings.

Use DNNs to build encoding models of EEG visual responses.

In this you will find simple and easy Computer Vision Codes in Python

In this we trained a model to detect if there is a tumor in the brain image given to the model. Meaning a model for binary class with an accuracy of above 90 for same and cross validation.

In this project we will train stable diffusion model on CIFAR10 dataset and then try to generate images form ten different classes.

We segmented the Brain tumor using Brats dataset and as we know it is in 3D format we used the slicing method in which we slice the images in 2D form according to its 3 axis and then giving the mod…

We segmented the Brain tumor using Brats dataset and as we know it is in 3D format we used the slicing method in which we slice the images in 2D form according to its 3 axis and then giving the mod…

In this project we will train our model on open and close eyes dataset then use that with face recognition library to check if the driver is sleeping or not.

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