wl935 Goto Github PK
Name: Weidong Lin
Type: User
Company: Durham University
Bio: PhDepression in Economics.
Location: Durham, UK
Name: Weidong Lin
Type: User
Company: Durham University
Bio: PhDepression in Economics.
Location: Durham, UK
post-processing experiments with neural networks
PyData 2018 tutorial for tidying data
Portfolio and risk analytics in Python
This package aims to compute conditional quantiles using random regression forests from the scikit-learn library.
Here is a [quantile random forest](http://jmlr.org/papers/v7/meinshausen06a.html) implementation that utilizes the [SciKitLearn](https://scikit-learn.org/stable/) RandomForestRegressor. This implementation uses [numba](https://numba.pydata.org) to improve efficiency.
Quantile Parametrization for probability distribution functions module
Quantile Regression of High-Frequency Data Tail Dynamics via a Recurrent Neural Network
A validation study for the application of quantile regression neural networks to Bayesian remote sensing retrievals
Predicting cloud top pressure from MODIS observations using QRNNs.
Tensorflow implementation of deep quantile regression
Qauntile autoregressive neural network for time series anamoly detection.
Quantile regression using keras multi output
Quantile regression neural networks
R package - Quantile Regression Forests, a tree-based ensemble method for estimation of conditional quantiles (Meinshausen, 2006).
A selection of MATLAB frunctions to estimate regime switching copula models
SeDuMi: A linear/quadratic/semidefinite solver for Matlab and Octave
Quantnet: validated SFE quantlets
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
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.
Using neural networks to predict stock price direction
TENET: Tail-Event driven NETwork Risk
QRNN (Quantile Regression Neural Network) Keras version
Q for Applied Quantitative Finance (3rd edition)
Probabilistic Load 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.