DorisYunzhuo's Stars
SheikhRabiul/A-Deep-Learning-Based-Illegal-Insider-Trading-Detection-and-Prediction-Technique-in-Stock-Market
Illegal insider trading of stocks is based on releasing non-public information (e.g., new product launch, quarterly financial report, acquisition or merger plan) before the information is made public. Detecting illegal insider trading is difficult due to the complex, nonlinear, and non-stationary nature of the stock market. In this work, we present an approach that detects and predicts illegal insider trading proactively from large heterogeneous sources of structured and unstructured data using a deep-learning based approach combined with discrete signal processing on the time series data. In addition, we use a tree-based approach that visualizes events and actions to aid analysts in their understanding of large amounts of unstructured data. Using existing data, we have discovered that our approach has a good success rate in detecting illegal insider trading patterns. My research paper (IEEE Big Data 2018) on this can be found here: https://arxiv.org/pdf/1807.00939.pdf
mtk12/IBM-Data-science-capstone-project
Real Estate Prices & Venues Data Analysis of London
john-james-ai/shinyHome
Real Estate Market Forecasting and Analytics
vinta/awesome-python
An opinionated list of awesome Python frameworks, libraries, software and resources.
watson-developer-cloud/visual-recognition-code-pattern
Anuken/Mindustry
The automation tower defense RTS