article thumbnail

Structural Evolutions in Data

O'Reilly on Data

” Each step has been a twist on “what if we could write code to interact with a tamper-resistant ledger in real-time?” While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.”

article thumbnail

Exploring US Real Estate Values with Python

Domino Data Lab

This post covers data exploration using machine learning and interactive plotting. Models are at the heart of data science. Data exploration is vital to model development and is particularly important at the start of any data science project. Interactive Data Visualization in Python. Introduction. fill=True,).:

article thumbnail

Using random effects models in prediction problems

The Unofficial Google Data Science Blog

Column "a" is an advertiser id, "b" is a web site, and "c" is the 'interaction' of columns "a" and "b". $y$ We have many routine analyses for which the sparsity pattern is closer to the nested case and lme4 scales very well; however, our prediction models tend to have input data that looks like the simulation on the right.