Tips for Succeeding in a CS Ph.D.
Or: Things I Wish I Knew Four Years Ago. A collection of lessons that took me longer to learn than I would have liked. Much of these are the soft skills needed to survive a Ph.D.
The Basic Math of Neural Networks
Some slides from a recent talk internal to our lab group at Clemson. Covers the absolute fundamentals of neural networks and back propagation.
Talks about how text embeddings and more typical neural networks are conceptually related.
Basic Iterative Numeric Optimization
Covers the very basics of iterative optimization.
Producer and Consumer Model in C++
Describes a pattern to write really easy parallel code using tasks in OpenMP.
Document Embedding Basics
Covers the basis of doc2vec, as well as other methods for learning latent representations of documents, extending the word embedding overview.
Agile Project Management in Google Sheets
Many small teams spend a lot of time and money on agile project management software. However, you can get a majority of the same function from free tools like Google Sheets.
Word Embedding Basics
Describes that mathematical basis of word2vec. A method of learning latent representations of natural language words.
Hypothesis Generation Explained
A sizable write up that details the basics of hypothesis generation, and how the Moliere project fits in.