VGG | Resnet | Alexnet | Squeezenet | Densenet | Inception

Cómo cambia la exactitud de un modelo, al usar diferentes capas de convolución y modificar el número de épocas y baches

A performance benchmark of recent image classification models in deep learning

2022학년도 2학기 인공지능개론 강의자료 및 Jupyter notebook 실습 파일입니다

This project is an implementation of the Detection Transformer (DETR) and the Conditional DETR variant of the model for state-of-the-art object detection. Using this project you can easily fine-tune and test both DETR variants on your own dataset following the included notebook guide.

In this notebook, we want to recognize the objects in the image using pre-trained models. The used models are fasterRCNN, RetinaNet, SSD and FCOS. The code is programmed in Python language and uses PyTorch and TorchVision library.

This GitHub laboratory contains PyTorch classification loss functions, Jupyter notebooks, and documentation for researchers and machine learning enthusiasts interested in deep learning and PyTorch.

Bloom is a project utilizing PyTorch and Jupyter notebooks to develop an image classifier for identifying different species of flowers using deep learning techniques.

This lab is provided by IBM and Cognivite Class. In this notebook, I have learned the basics of tensor operations and ccompare tensors with vectors and numpy arrays.

This repository contains Jupyter notebooks demonstrating image classification using pretrained deep learning models in PyTorch. The main example uses GoogleNet for classifying bean leaf lesions, leveraging transfer learning for improved accuracy and efficiency

Este repositório contém todos os códigos realizados durante a formação Inteligência Artificial na Data Science Academy. Os códigos foram feitos em Python através do Jupyter Notebook e contém comentários detalhados sobre o passo a passo para uma análise preditiva com Deep Learning.

Histopathology image classification to predict molecular subtypes. Includes datasets, EDA and preprocessing notebooks, patch extraction, baseline models, and training utilities for quick experiments and reproducible evaluation. Project for the Artificial Neural Networks and Deep Learning course at Politecnico di Milano (PoliMi) (2025/2026).

This repository serves as a personal practice space for mastering PyTorch fundamentals. It contains notebooks and code snippets covering essential PyTorch concepts, including tensors, autograd, neural networks, and more. The repository aims to help learners develop hands-on experience with PyTorch through practical exercises and projects.