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

CIFAR 10 image dataset

Covid-19 detection in chest x-ray images using Convolution Neural Network.

Deep Learning

Fortran backward (reverse) mode automatic differentiation.

Compare vanishing gradient problem case by case.

This program implements logistic regression from scratch using the gradient descent algorithm in Python to predict whether customers will purchase a new car based on their age and salary.

Simple multi layer perceptron application using feed forward back propagation algorithm

Test project for neural networks - Handwritten digit recognition on MNIST dataset

A classical XOR neural network using pytorch

A repository with Twitter data and tweet classifiers using several machine learning approaches to measure the accuracy and performance of the approaches on classifying tweets.🐧

A neural network (NN) having two hidden layers is implemented, besides the input and output layers. The code gives choise to the user to use sigmoid, tanh orrelu as the activation function. Prediction accuracy is computed at the end.

Neural Network from scratch without any machine learning libraries

Logit function.

Create an iterator which evaluates the logit function for each iterated value.

Standard logistic function.

This is an ongoing project intended to make it easier to use neural network creation, genetic algorithms, and other data science and machine learning skills.

Gradient descent is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. To find a local minimum of a function using gradient descent, we take steps proportional to the negative of the gradient (or approximate gradient) of the function at the current point. But if we instead take steps proporti…

ml5 (friendly machine learning for the web) SharePoint Framework (SPFx) extension