Writings

Below you can find my writings on machine learning, data science, and technology. Enjoy!
Lab41 Reading Group: Skip-Thought Vectors
Word embeddings are great and should be your first stop for doing word based NLP. But what about sentences? Read on to learn about skip-thought vectors, a sentence embedding algorithm!
Jupyter Notebooks: Not for Development
Jupyter Notebooks are great for a lot of things; development of code is not one of them.
WhereTo.Photo: Using Data Science to Take Great Photos
Where is the best spot to take a photo in San Francisco? Learn how I answered this question with my Insight Data Science project!
Lab41 Reading Group: Deep Residual Learning for Image Recognition
Inception, AlexNet, VGG... There are so many network architectures, which one should you be using? The one everyone else is: ResNet! Come find out how it works!
Lab41 Reading Group: Deep Compression
Deep learning is the future, but how can I fit a battery-drain, half-gigabyte network on my phone? You compress it! Come find out how deep compression saves space and power!
Lab41 Reading Group: Deep Networks with Stochastic Depth
Dropout successfully regularizes networks by dropping nodes, but what if we went one step further? Find out how stochastic depth improves your network by dropping whole layers!
SAT2Vec: Word2Vec Versus SAT Analogies
Could Word2Vec pass the SAT analogies section and get accepted to a good college? I take a pre-trained model and find out!
Dragon Farkle: Simulating the End Game
How many soldiers do you need to successful defeat the dragon in Dragon Farkle, and how likely to succeed is your attack? I find out by simulating a game of Dragon Farkle!
Further Double-checking FiveThirtyEight's 2016 Primary Predictions
Is FiveThirtyEight's Polls Plus model biased against any candidate? I continue my double-checking their model by looking at each candidate individually.
Lab41 Reading Group: Generative Adversarial Nets
What cost function would you use to determine if a picture looks real? How about one learned by another network! Find out more with my summary of Generative Adversarial Networks!