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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).
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.
This is the official repository of L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning github
An Image Classification project w/ MobileNetV2 and DenseNet-121. Leveraging techniques like Hyperparameter Tuning, Transfer Learning, Imagine Preprocessing Techniques and Ensemble Methods.
A project is a second part of Introduction to Machine Learning course. Here the problem is image recognition on CIFAR10 dataset using 2 different approaches: simple model and transfer learning using pretrained model.
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.
RayFedAI is an open-source federated learning framework that harnesses the power of distributed computing with the Ray backend. This project aims to provide a robust platform for implementing and training machine learning models across decentralized data sources while maintaining data privacy and security.