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time series analysis
Feature Engineering for Time Series Analysis – ODSC East 2018
What is a time series analysis in data science? How can you construct an effective time series analysis? What does feature engineering have to do with time series analysis? These questions and more were many of the talking points from the talk by Michael Schmidt, PhD, Chief Scientist at DataRobot... Read more
Time Series Analysis with Generalized Additive Models
Whenever you spot a trend plotted against time, you would be looking at a time series. The de facto choice for studying financial market performance and weather forecasts, time series are one of the most pervasive analysis techniques because of its inextricable relation to time—we are always interested to foretell the... Read more
Time Series Analysis with Generalized Additive Models
Whenever you spot a trend plotted against time, you would be looking at a time series. The de facto choice for studying financial market performance and weather forecasts, time series are one of the most pervasive analysis techniques because of its inextricable relation to time—we are always interested to foretell... Read more
A Different Use of Time Series to Identify Seasonal Customers
I had previously written about creatively leveraging your data using segmentation to learn about a customer base.  The article is here.  In the article I mentioned utilizing any data that might be relevant.  Trying to identify customers with seasonal usage patterns was one of the variables that I mentioned that sounded interesting.   And... Read more
Reel Reviews: Neural Networks for Sentiment Analysis
This is a joint article authored in collaboration between Kannan Sankaran and Win Suen. The Problem Over the past few years, there has been burgeoning interest in neural networks from data science and engineering communities. The advent of ever larger datasets, efficient commodity hardware, and powerful open source libraries have... Read more
Demystifying Black-Box Models with SHAP Value Analysis
As an Applied Data Scientist at Civis, I implement the latest data science research to solve real-world problems. We recently worked with a global tool manufacturing company to reduce churn among their most loyal customers. A newly proposed tool, called SHAP (SHapley Additive exPlanation) values, allowed us to build a complex... Read more
Machine Learning Helps Humans Perform Text Analysis
The rise of Big Data created the need for data applications to be able to consume data residing in disparate databases, of wildly differing schema. The traditional approach to performing analytics on this sort of data has been to warehouse it; to move all the data into one place under... Read more
In the 1840’s Dr. Ignaz Semmelweis had a big problem on his hands. He was an obstetrician in the Vienna General Hospital and healthy young women in the maternity ward were dying at an alarming rate. The problem was well known throughout Vienna. There were two wards, we’ll call them... Read more
In a recent post, I offered a definition of the distinction between data science and machine learning: that data science is focused on extracting insights, while machine learning is interested in making predictions. I also noted that the two fields greatly overlap: I use both machine learning and data science in... Read more
Exploratory Data Analysis of Tropical Storms in R
Exploratory Data Analysis of Tropical Storms in R The disastrous impact of recent hurricanes, Harvey and Irma, generated a large influx of data within the online community. I was curious about the history of hurricanes and tropical storms so I found a data set on data.world and started some basic Exploratory data... Read more
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