In my pursuit of machine learning research, I often delve into small-sample, high-dimensional bioinformatics datasets.
Read More
Bye Bye, Jekyll. Hello, Hugo
I’ve decided to bid farewell to Jekyll after encountering one too many Liquid errors and dealing with the Ruby dependency headache.
Read More
Installing TensorFlow on an AWS EC2 Instance with GPU Support
Here’s a guide on installing TensorFlow 0.6 on an Amazon EC2 Instance with GPU Support. Additionally
Read More
Serverless API around Google Cloud Vision with the Serverless Framework
Recently, the Serverless Framework reached version 1.0 (beta) after about a year of development.
Read More
Configuring IPython Notebook Support for PySpark
Apache Spark is a powerful tool for handling large-scale data processing, and PySpark offers a convenient way to interact with Spark using Python.
Read More
A Brief Look at Mixture Discriminant Analysis
In my recent postdoctoral work focusing on data-driven automated gating, I’ve been extensively exploring finite mixture models.
Read More
Installing Python Data Science Stack on Yosemite
While setting up a Python data-science stack within a fresh virtual environment on my Mac running OS X 10.10.1 (Yosemite)
Read More
High-Dimensional Microarray Data Sets in R for Machine Learning
My primary focus in machine learning research revolves around analyzing small-sample, high-dimensional bioinformatics data sets.
Read More
How to Download Kaggle Data with Python and requests.py
Lately, I’ve been delving into Kaggle and found myself frustrated with the manual data download process via their website.
Read More
Setting Up the Development Version of R
At Fred Hutchinson, my colleagues often utilize the development version of R, known as R-devel, and have encouraged me to follow suit. In this post
Read More