jdc08161063 Goto Github PK

ssd_tensorflow_traffic_sign_detection

Implementation of Single Shot MultiBox Detector in TensorFlow, to detect and classify traffic signs

ssenet-pytorch

The pytorch implementation of self-supervised scale equivariant network for weakly supervised semantic segmentation.

ssgan-tensorflow

A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks.

ssgrl

ssh

SSH: Single Stage Headless Face Detector

st-gcn

Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch

stackgan

stage

工程与学术笔记

stair-actions

Large Scale Video Dataset for Action Recognition

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

stanford_self_driving_car_code

Stanford Code From Cars That Entered DARPA Grand Challenges

stanfordquadruped

stargan-tensorflow

Simple Tensorflow implementation of StarGAN (CVPR 2018 Oral)

statistical-learning

Lecture Slides and R Sessions for Trevor Hastie and Rob Tibshinari's "Statistical Learning" Stanford course

stc2

Demo code for the paper STC2 which released three short text datasets for clustering and classification

steal

STEAL - Learning Semantic Boundaries from Noisy Annotations

stereo-magnification

Code accompanying the SIGGRAPH 2018 paper "Stereo Magnification: Learning View Synthesis using Multiplane Images"

stereo-rcnn

Code for 'Stereo R-CNN based 3D Object Detection for Autonomous Driving' (CVPR 2019)

stgan

STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing

stgcn_ijcai-18

Spatio-Temporal Graph Convolutional Networks

stmn

[ECCV 2018] Spatial-Temporal Memory Networks for Video Object Detection

stn-ocr

Code for the paper STN-OCR: A single Neural Network for Text Detection and Text Recognition

stochastic-deep-networks

Stochastic Deep Networks

stock-rnn

Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.

stock-selection-a-framework

This project demonstrates how to apply machine learning algorithms to distinguish "good" stocks from the "bad" stocks.

stock2vec

Stock embeddings based on PE context

stock_market_prediction

This is the code for "Stock Market Prediction" by Siraj Raval on Youtube

stock_market_reinforcement_learning

This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

stopwords

中文常用停用词表（哈工大停用词表、百度停用词表等）