Digests » 94

this week's favorite

160+ Data Science Interview Questions

In this post, I’d like to summarize all my interviewing experience  —  from both interviewing and being interviewed  —  and came up with a list of 160+ theoretical data science questions.

Poké-Agent: Pokemon Battling & Machine Learning

Machine learning models have beaten humans at many games — but not Pokemon. Let’s fix that.

Levenshtein Transformer

Modern neural sequence generation models are built to either generate tokens step-by-step from scratch or (iteratively) modify a sequence of tokens bounded by a fixed length. In this work, we develop Levenshtein Transformer, a new partially autoregressive model devised for more flexible and amenable sequence generation.

End to End Machine Learning with Python

Learn how to build and deploy a machine learning application from scratch. An end-to-end tutorial on data scraping, modeling, and deployment.

Gradient Descent from scratch

Gradient Descent is one of the most fundamental optimization techniques used in Machine Learning. But what is a gradient? On what do we descent down and what do we even optimize in the first place?