Ensemble learning which included multiple learners, i.e. Machine Learning algorithms, may take much longer time than expected to develop. When using a search grid for parameter optimization to train an ensemble, depending on the included algorithms, the number of variables, and the corresponding iterations based on combinations of parameter settings and with cross validation, it may take a… Continue reading R Parallel Processing for Developing Ensemble Learning with SuperLearner
This is an app developed with Shiny and R for visualizing real-time data stream. In this recording, the app ran locally, while I downloaded raw data collected from a set of Raspberry Sensor Hat devices stored in Azure cloud storage to a local disk to mimic a data pipeline for acquiring data with a batch processing. In production,… Continue reading A Shiny App for Monitoring Real-Time Data Stream
House Price Prediction This project was to develop a Machine Learning model for predicting a house price. Despite there were a number of tree-based algorithms relevant to this application, the project was to examine linear regression and focused on specifically four models: Linear Regression, Ridge Regression, Lasso Regression and Elastic Net. Overview Data Analysis Feature… Continue reading Predicting House Price with Multiple Linear Regression
Data Preparation of Diabetes Dataset Due to web page limitation, this post has been moved to https://yungchou.github.io/site/
Why When developing a Machine Learning model, if there is a significant number of features to inspect, an initial and manual Exploratory Data Analysis may become tedious and nonproductive. One option is to facilitate the process by testing and identifying important variables based on statistical methods to help trim down features. And that is where… Continue reading Feature Selection with Help from Boruta
Here’s my presentation at Techno Security & Digital Forensics Conference 2018. Click the zoom level (%) for a full-page view or the dropdown menu to download the pdf.
The concept of software supply chain is not a new one. What may be new is that CI/CD (Continuous Integration/Continuous Delivery) with containers makes it conceptually easy to understand and technically practical to implement. Here’s a process diagram illustrates this approach with five steps. CI/CD Process A software supply chain is here the “master” branch… Continue reading A Secure Software Supply Chain with Containers