校招、秋招、春招、实习好项目！带你从零实现一个高性能的深度学习推理库，支持大模型 llama2 、Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step

Compute Sentence Embeddings Fast!

Hi! Thanks for checking out my tutorial where I walk you through the process of coding a convolutional neural network in java from scratch. After building a network for a university assignment, I decided to create a tutorial to (hopefully) help others do the same and improve my own understanding of neural networks.

An algorithm that facilitates communication between a speech-impaired person and someone who doesn't understand sign language using convolution neural networks

Kaggle Machine Learning Competition Project : In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset of Zalando's article images

implementation of neural network from scratch only using numpy (Conv, Fc, Maxpool, optimizers and activation functions)

This repository consists of models of CNN for classifying different types of charts. Moreover, it also includes script of fine-tuned VGG16 for this task. On top of that CradCAM implementation of fine-tuned VGG16.

**DeepLearning** (CNN, RNN) + Bayesian Neural Network

Given an image of a dog, our algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.

This repository provides a smooth max pooling implementation using the LogSumExp (LSE) function. Unlike traditional max pooling, which can result in sparse gradients, our approach approximates the maximum operation to ensure more effective gradient distribution.

Using convolutional neural networks to build and train a bird species classifier on bird pics data with corresponding species labels, also build GUI for the same.

Written by Sem Kirkels, Nathan Bruggeman and Axel Vanherle. Grayscales an image, applies convolution, maximum pooling and minimum pooling.

In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset.

This repository contains code that implemented Mask Detection using MobileNet as the base model and Neural Network as the head model. Code draws a rectangular box over the person's face in red if no mask, green if the mask is on, with 99% accuracy in real-time using a live webcam. Refer to README for demo

In this project, we use CNN to classify Fashion MNIST data into different categories.

This model helps us classify 10 different real-life objects by undergoing training under tensorflow's CIFAR dataset which contains 60,000 32x32 color images with 6000 images of each class. I have made use of a stack of Conv2D and MaxPooling2D layers followed by a few densely connected layers.