Tests I am performing on a Python package for building residual multi - layer perceptrons and tandem [any model] -> ResMLPs models, useful for effective transfer learning. A pypi package should be coming soon.

This project implements AlexNet, a pioneering convolutional neural network architecture, using PyTorch. The implementation is based on the original paper by Krizhevsky et al. (2012).

This project focused on the analysis of the sleep, activity, food intake, and loop activity of a very small sample of students

Implements MobileViT and ViT from scratch, compatible with graph execution mode in tensorflow. Compares multiple cnn and transformer-based models including VGG, ResNet, ViT and MobileViT on a small data set.

A deep learning based domain knowledge integration for small dataset

This repo contains previous years' codejam solutions

Research log for Clastic Music

A deep learning based domain knowledge integration for small dataset

Cancer detection through a blood test (CancerSEEK) using machine learning techniques.

A dataset for 12 Iranian weed species is provided and several Deep Learning pre-trained models are utilized for the multi-class classification task.

Homework on training deep networks with very small data - MVA MSc

Attempt to predict the median price of homes in a given Boston suburb in the mid-1970s, given data points about the suburb at the time, such as the crime rate, the local property tax rate, and so on. Only 506 data points, split between 404 training samples and 102 test samples. Each feature in the input data (for example, the crime rate) has a d…

Code for the paper "An Empirical Analysis of KDE-based Generative Models on Small Datasets"

My solution of dirty/cleaned plates recognition kaggle task

Mixture of Experts from scratch

Experiments with artificial neural networks on small datasets.

This repository contains Alzheimer's detection model using few-shot learning and a machine learning ensemble model. With limited samples, the few shot learning enables efficient detection and the ensemble model incorporates the advantages of multiple algorithms improving the efficiency of detection.

Project to scrape CFTC.gov reports and present using Power Query & Power Pivot

AutoML tool for imbalanced and small tabular datasets