Terence Shin
Data scientist at Koho
Expertise: Data science, software engineering perspectives
Education: Georgia Institute of Technology; Quantic School of Business and Technology; Queen's University

Terence Shin is a data scientist at Koho.

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Two employers interviewing a job candidate in office
Data science interviews encompass a variety of challenging questions to test your knowledge in machine learning, probability, SQL and more. Hone your skills with these questions.
Packages on an assembly line representing model deployment
Model deployment is the process of integrating a machine learning model into a production environment where it can take in an input and return an output.
Machine learning engineering selecting features in a data stream
Feature importance involves calculating a score for all input features in a machine learning model to determine which ones are the most important. Here’s how to do it.
Two data scientists creating a machine learning model on computer
Machine learning models are categorized as either supervised or unsupervised. Here’s what you need to know about each model and when to use them.
A man wears a headset and works on code at a desktop
Learn 10 advanced SQL concepts you should know for data science interviews to take your SQL skills to the next level.
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Collect unbiased data utilizing these four types of random sampling techniques: systematic, stratified, cluster, and simple random sampling.
A woman works on multiple computer monitors manipulating data
Statistical bias is when a model or statistic is unrepresentative of the population. There are six main types of bias in statistics.