Super-Convergence on CIFAR10

CAI NEURAL API - Pascal based deep learning neural network API optimized for AVX, AVX2 and AVX512 instruction sets plus OpenCL capable devices including AMD, Intel and NVIDIA.

Study of the impact of a Randomized ReLU function on the performance of a neural network model.

This projects aims at implementation and training of different orientations and types of Neural Networks with respect to Mathematical equations and problems ranging from a simple straight forward equation to a bit complex equations in nature too. Following a comparative study on how different architectures react with these problems.

Implementing Transfer Learning using Resnet18. Training and testing Resnet18 on Even numbered Classes in CIFAR10 Dataset.

CIFAR-10 trained with CreateML and a SwiftUI app for real time model testing. Kaggle Score: 0.69660

A summative coursework for CSC8635 Machine Learning with Project

A lightweight and extensible toolbox for image classification

Official PyTorch Implementation for the "Distilling Datasets Into Less Than One Image" paper.

Experiments on CIFAR-10 classification

Quick guide to submitting and monitoring jobs on Ozerlabs slurm cluster.

A PyTorch implementation of "EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks".

A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.

Программы по дисциплине "Современные методы глубокого машинного обучения" 6 семестра ФИТ НГУ

Implemented ConvNext and tested with CIFAR-10

There are plenty of ways to approach supervised learning: Some of them being Neural Networks, Convolutional Neural Networks and Residual Networks. In this repository we develop an in depth analysis of the difference between these on the CIFAR10 dataset using Jupyter Notebooks and Pytorch.

This repository showcases two approaches to the coulourization task of CIFAR10 images: Auto Encoder U-Nets and Deep Conditional Generative Adversarial Networks (DCGANs).

This is the official repository of L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning github

This is the repository containing machine learning and deep learning projects, as well as some presentation slides on these topics.

An Image Classification project w/ MobileNetV2 and DenseNet-121. Leveraging techniques like Hyperparameter Tuning, Transfer Learning, Imagine Preprocessing Techniques and Ensemble Methods.