ddkrsiten's starred repositories
spring-boot-examples
about learning Spring Boot via examples. Spring Boot 教程、技术栈示例代码，快速简单上手教程。
GRU4REC-pytorch
An other implementation of GRU4REC using PyTorch
learning_research
本人的科研经验
SASRec.pytorch
PyTorch(1.6+) implementation of https://github.com/kang205/SASRec
neural-collaborative-filtering
pytorch version of neural collaborative filtering
RecBole-CDR
This is a library built upon RecBole for cross-domain recommendation algorithms
age-gender-estimation
Keras implementation of a CNN network for age and gender estimation
gender-recognition
TensorFlow CNN卷积神经网络实现人脸性别检测
FaceRecognition-tensorflow
基于TensorFlow训练的人脸识别神经网络
cnn_captcha
use cnn recognize captcha by tensorflow. 本项目针对字符型图片验证码，使用tensorflow实现卷积神经网络，进行验证码识别。
stock_cnn_blog_pub
This project is a loose implementation of paper "Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach"
Stanford-Project-Predicting-stock-prices-using-a-LSTM-Network
Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).
neuraltalk
NeuralTalk is a Python+numpy project for learning Multimodal Recurrent Neural Networks that describe images with sentences.
spacenet_building_detection
Project to train/test convolutional neural networks to extract buildings from SpaceNet satellite imageries.
CarND-Project5-Vehicle_Detection_and_Tracking
Vehicle Detection with Convolutional Neural Network
speech-recognition-neural-network
This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.
Deep-Neural-Networks-HealthCare
Tangible and Practical Deep Learning Projects Repository for Healthcare such as Cancer, Drug Discovery, Genomic and More
MachineLearing
ML算法&项目
recurrent-neural-networks
Learning about and doing projects with recurrent neural networks
Machine-Learning-by-Andrew-Ng-in-Python
Documenting my python implementation of Andrew Ng's Machine Learning course