Boost your ML research by using this video event segmentation tool for qualitatively coding your video clips

Photo by Vanilla Bear Films on Unsplash

Analyzing video recordings of human and animal behaviors has been a powerful tool for researchers across disciplines.

In recent years, computer vision and machine learning advances have greatly facilitated automated video analyses (e.g. object detection, facial expressions, poses). …

A Data Science Tutorial

Tutorial on what metrics to use and how to calculate significance when measuring the similarity between matrices

Correlation matrices. Figure produced by author.

Comparing the similarity between matrices can offer a way to assess the structural relationships among variables and is commonly used across disciplines such as neuroscience, epidemiology, and ecology.

Let’s assume you have data on how people react when watching a short Youtube video. This could be measured by facial expressions

According to science

The answer is more simple than you think

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We’ve all seen those people at the gelato shop. The ones who can’t decide what they want. They try every single flavor and perseverate whether they want Vanilla or Chocolate until the queue behind them send glaring looks.

This kind of decision paralysis creep up not only in gelato parlors…

Become a better data scientist

Watching Data Scientists solve new datasets can be educational, entertaining, and an immersive experience.

Photo by Nikolai Chernichenko on Unsplash

#SLICED is a 2-hour data science competition streamed by Nick Wan and Meg Risdal on Twitch. Contestants code in real time exploring, cleaning, and analyzing a never-seen dataset to win the most points for training a model with the best prediction accuracy and data visualization.

I stumbled on #SLICED when…

Hands-on Tutorials

Tutorial on how to run Linear Mixed Effects Regressions (LMER) models in Python and Jupyter Notebooks

Photo by Forest Simon on Unsplash

One of the reasons I could not fully switch out of R to Python for data analyses was that linear mixed effects models were only available in R. Linear mixed effects models are a strong statistical method that is useful when you are dealing with longitudinal, hierarchical, or clustered data…

Jin Hyun Cheong, PhD

Human behavior & machine learning enthusiast || Cognitive Neuroscience PhD turned data nerd || http://jinhyuncheong.com/

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