August 14, 2017

Word Embeddings in the Pāli Canon

Is there a point where Buddhism and artificial intelligence could converge? Yes, there are already some perspectives on how a religion so grounded in the human conscious experience would regard a hypothetical sentient machine; one can only wonder how such an alien intelligence would itself consider introspective practices created by and for our own organic minds. A more practical starting point might be using machine learning to help us understand Buddhism, especially those of us in parts of the world to which it has only been introduced within the past few generations. more

March 6, 2017

Logistic Regression

This is the second in a series of posts in which I explore concepts in Andrew Ng’s Introduction to Machine Learning course on Coursera. In each, I’m implementing a machine learning algorithm in Python: first using standard Python data science and numerical libraries, and then with TensorFlow. Logistic regression is similar to linear regression, but instead of predicting a continuous output, classifies training examples by a set of categories or labels. more

February 26, 2017

Linear Regression

This is the first of a series of posts in which I’ll be exploring concepts taught in Andrew Ng’s Introduction to Machine Learning course on Coursera. As a CS student, I enjoyed doing odd or extra things with my assignments — I found it added a greater challenge and allowed me to learn outside the scope of the class in a well-structured way. So, as I progress through this course, I’ll be posting another take on the coursework in Python, using a Jupyter notebook. more