Michael Galarnyk
Developer Relations at Intel and cnvrg.io
Expertise: Data science and engineering
Education: University of California San Diego
Michael Galarnyk works in developer relations at Intel and cnvrg.io, the company behind the Ray Project. Galarnyk served as an instructor with Stanford Continuing Studies and has been working in data science since 2013. He holds a master’s degree in data science and engineering from UC San Diego and a bachelor’s degree in nanoengineering.
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Python lists store an ordered collection of items that can be of different types. After defining a list, it’s possible to update the individual items in a list. Here’s how.
This Python dictionary tutorial covers how to define and access values in a dictionary, how to iterate through a dictionary and various dictionary methods.
Principal component analysis (PCA) in Python can be used to speed up model training or for data visualization. This tutorial covers both using scikit-learn.
A z-table, or standard normal table, reveals what percentage of values fall below a certain z-score in a normal distribution. Here’s how to use one and create your own.
Boxplots are graphs that tell you how your data’s values are spread out. Here’s how to read a boxplot and even create your own.
The empirical rule, also known as the 68-95-99.7 rule, represents the spread of data within a normal distribution. Here’s what you need to know.
Train test split is a model validation procedure that reveals how your model performs on new data. Here’s how to apply it.