montshasta2020 Goto Github PK
Name: Mont Shasta Corp
Type: User
Name: Mont Shasta Corp
Type: User
Anomaly detection for streaming time series, featuring automated model selection.
Transfer Learning from Synthetic to Real-Noise Denoising with Adaptive Instance Normalization (CVPR 2020)
The project involved using mining time-series data and analyzing it to find small motifs or anomalous signatures. To this end, we used common anomaly detection tools such as Isolation Forest, Extended Isolation Forest, Eamonn Keogh’s Matrix Profile and Auto Encoder neural network. We created a graphical UI to allow a broad range of company employees to use it for exploring our findings. In the next project of the company (further research) the company aims to correlate our findings with pollution or maintenance related behavior patterns.
List of tools & datasets for anomaly detection on time-series data.
Back test
Python Backtesting library for trading strategies
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
This notebook demonstrates the use of the pandas library to perform some basic analysis on risk and reward of stock funds.
Batch-Instance Normalization (BIN)
TensorFlow code and pre-trained models for BERT
Brian is a free, open source simulator for spiking neural networks.
Ablation Study of CapsuleNetwork on TimeSeries
Bag-of-Features Pooling for Deep Convolutional Neural Networks
Python package for linear and quadratic programming
Generative Adversarial Network for Stock Market Price Prediction
Master Thesis: Limit order placement with Reinforcement Learning
Deep Adaptive Input Normalization for Time Series Forecasting
A python library for easy manipulation and forecasting of time series.
Making predictions on prices in the Deutsche Börse Public Dataset using neural networks
A deep learning model for Financial Signal Representation and Trading
Datasets, papers and books on AI & Finance.
PyTorch implementation of the CVPR 2018 paper Deep Image Prior by Dmitry Ulyanov et. al.
Stock for Deep Learning and Machine Learning
Deep RL stock trading agent
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
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.