fagan2888 Goto Github PK
Type: User
Location: New York
Type: User
Location: New York
Experiments for AAAI anchor paper
Anderson acceleration for the alternating projections method for the nearest correlation matrix problem
Andrew Ng's Deep Learning (Machine Translation with GRU Attention, Car Detection with YOLO, Face Recognition with Siamese)
A tool to re-construct valid AngularJS stacktraces.
Animal Segmentation using Markov Random Field
Benchmarks of approximate nearest neighbor libraries in Python
The analysis and prediction of macroeconomic time-series is a factor of great interest to national policymakers. However, economic analysis and forecasting are not simple tasks due to the lack of a precise model for the economy and the influence of external factors, such as weather changes or political decisions. Our research is focused on Spanish speaking countries. In this thesis, we study different types of neural networks and their applicability for various analysis tasks, including GDP prediction as well as assessing major trends in the development of the countries. The studied models include multilayered neural networks, recursive neural networks, and Kohonen maps. Historical macroeconomic data across 17 Spanish speaking countries, together with France and Germany, over the time period of 1980-2015 is analyzed. This work then compares the performances of various algorithms for training neural networks, and demonstrates the revealed changes in the state of the countries’ economies. Further, we provide possible reasons that explain the found trends in the data.
An artificial machine learning program that attempts to impersonate the writing style of any given text training set
Artificial Neural Network - Corporate Investment Grade Bond Rating
Experimental Reinforcement Learning Architecture
Generate the symbolic expression of a Matlab Neural Network object
Based on the Stanford's blog
Annotation Tools Modifed from https://github.com/cs-chan/Total-Text-Dataset
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
Python API for Annual Company Data using Quandl
In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.
An implementation of an unsupervised method of detecting anomalous text called "Distance to the Textual Complement"
Anomaly detection related books, papers, videos, and toolboxes
Change your IP address instantly - easy small GUI tool for Windows (linux soon)
A module to manage various properties of XML documents
Repository containing code for visualizing Ant Colony Optimization algorithms for clustering
Ant Colony Optimization for Travelling Thief Problem
Persist Pandas objects within a MongoDB database
越来越多的网站具有反爬虫特性,有的用图片隐藏关键数据,有的使用反人类的验证码,建立反反爬虫的代码仓库,通过与不同特性的网站做斗争(无恶意)提高技术。(欢迎提交难以采集的网站)(因工作原因,项目暂停)
A Python library for time series forecasting
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.