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Video Tutorial

Do you know why the output of the sigmoid function can be interpreted as a probability?

Flying over Lake Tahoe, Spring 2018, picture taken by me with DJI Mavic Air

If you have taken any machine learning courses before, you must have come across logistic regression at some point. There is this sigmoid function that links the linear predictor to the final prediction. Depending on the course, this sigmoid function may be pulled out of thin air and introduced as…


The handiest visual note of PCA

Photo by Jonny Clow on Unsplash

Nowadays, the knowledge depth of data scientists and ML engineers is often judged by their regurgitation of the math and implementation details of an algorithm. I disagree with this approach. The reality is, nobody can remember every detail, and that’s okay. You don’t need to know how to implement an…

How to get started building Alexa skills for things you are too lazy to search online

Photo by Jason Leung on Unsplash

I moved to New York City from California two years ago. Having been spoiled by the Californian sunshine and nice weather for several years, I forgot how it’s like living in a city with a lot of precipitation. Sometimes I feel the rain never stops. No matter what season it…

The road to end-to-end data scientist/machine learning engineer

Photo by Robert Bye on Unsplash

Earlier this year I came across a viral Twitter thread by Randall Kanna about how to create one’s own computer science degree with free online content. It was not only excellent for people who don’t have prior knowledge in computer science, it’s also valuable for new software engineers who didn’t…


A short probability and algorithm tutorial that’s worth your while

Photo by Miikka Luotio on Unsplash

When you want some values from a certain probability distribution, say, a normal distribution, you could simply call rnorm in R, or numpy.random.normal in Python. But have you ever wondered how they do it under the hood? The underlying idea is incredibly simple yet powerful. In this article, I'm going…

By implementing your own deep learning framework in Python

Photo by Andre Ouellet on Unsplash

As the beating heart of deep learning, a solid understanding of backpropagation is required for any deep learning practitioner. Although there are a lot of good resources that explain backpropagation on the internet already, most of them explain from very different angles and each is good for a certain type…

From Animation to Intuition

Flying over Storm King Art Center in New York, Summer 2018. Photo by me on DJI Mavic Air

Update: I have ported the code to a Python package here. Feel free to experiment and produce similar plots like the ones in this post!

In the previous post, I showed some animated plots for the training process of linear regression and logistic regression. Developing a good “feel” of how…

From Animation to Intuition

This is one post in a series for machine learning optimization animations. Each plot can serve as a flashcard for easy consumption.

Long Island, Spring 2019
Flying over Town Beach near the tip of Long Island, Spring 2019. Picture taken by me with DJI Mavic Air.

If you are like me, you may prefer looking at pictures that move to pages of Greek symbols when it comes to learning math. It’s more intuitive, more…

Logan Yang

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