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A Tensorflow implementation of Semi-supervised Learning Generative Adversarial Networks (NIPS 2016: Improved Techniques for Training GANs).
SSH: Single Stage Headless Face Detector
This is a tensorflow re-implementation of SSH: Single Stage Headless Face Detector.
[IJCAI18] SSR-Net: A Compact Soft Stagewise Regression Network for Age Estimation
[IJCAI18] SSR-Net: A Compact Soft Stagewise Regression Network for Age Estimation
Single Shot Tracker
Repository for paper: Saliency-Based Spatio-Temporal Attention for Video Captioning
Single Shot Text Detector with Regional Attention
Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch
StackNet is a computational, scalable and analytical Meta modelling framework
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Scans genome contigs against the ResFinder and PointFinder databases.
Learning embeddings for classification, retrieval and ranking.
Start UiPath Robot from Salesforce
This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.
SteganoGAN is a tool for creating steganographic images using adversarial training.
Encodes text files into the pixel data of images
Code from the book: "Esteganografía y Estegoanálisis, Ed 0xWord"
Using a MRF with loopy belief propagation to infer depth from stereo images.
Free Bootstrap Admin Template
Free Bootstrap Admin Template for CodeIgniter
Keras implementation for "Deep Networks with Stochastic Depth" http://arxiv.org/abs/1603.09382
Building an option trading dashboard with Python
Stock Market Prediction using Numerical and Textual Analysis using Random Forest and VADER (nltk)
Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news article. Comparisons were made between the actual stock prices and the sentiment scores. Naive Bayes, OneR and Random Forest algorithms were used to observe the results of the model using Weka
Stock Prediction using machine learning
Predicting Stocks using SVM
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.