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Machine Learning for Time Series Data
Most organizations generate time-series data. The generation of sales data and financial data are primary components of all organizations’ business. This data is a form of time series data. Time series data consists of any data that carries a temporal component with it. Time series data is data that... Read more
A Practitioner’s Guide To Interrupted Time Series
In the world of causal inference, Randomized Controlled Trials, RCTs, are considered the gold standard as it rules out any covariate differences before the intervention. However, running an RCT isn’t an option for multiple reasons (e.g., too expensive, invalid assumptions, too long, not ethical, etc.). [Related Article: Discovering 135... Read more
Interpreting the 2020 Puerto Rico Earthquake Swarm with Data Science
Using visualizations, maps, time series and Google Trends data science, Puerto Rico earthquakes are described. Since late December 2019 until early January 2020, the southwestern region of the island Puerto Rico has been experiencing a series or swarm of earthquakes, leaving in its wake a trail of destruction and... Read more
Discovering 135 Nights of Sleep with Data, Anomaly Detection, and Time Series
In this article, I look at data from 135 nights of sleep and use anomaly detection and time series data to understand the results. Three things are certain in life: death, taxes, and sleeping. Here, we’ll talk about the latest. Every night*, us humans, after a long day of... Read more
Reading Tea Leaves: Principles of Predictive Analytics and the Path to Time-Series Predictions
Scott is presenting at ODSC East 2019 this May in Boston! Check out his workshop “Real-ish Time Predictive Analytics with Spark Structured Streaming.” With the advent of so many wonderful open-source tools and frameworks for machine learning & deep learning,  it can sometimes be difficult to understand just what... Read more