October 2019

The secular Bayesian: Using belief distributions without really believing

The secular Bayesian: Using belief distributions without really believing

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The religious Bayesian My parents didn’t raise me in a religious tradition. It all started to change when a great scientist took me under his wing and taught me the teachings of Bayes. I travelled the world and spent 4 years in a Bayesian monastery in Cambridge, UK. This particular place practiced the nonparametric Bayesian doctrine. We were religious Bayesians. We looked at the world and all we saw the face of Bayes: if something worked, it did […]

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Implementing AI algorithms in GPUs and CPUs // Intro to AI Accelerators! :)

Implementing AI algorithms in GPUs and CPUs // Intro to AI Accelerators! :)

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Ok so today my professor decided to tell us a Halloween joke, and I thought it was the funniest thing ever: “What is the circumference of a jack-o-lantern divided by its diameter??” Pumpkin pi !!!!!!!!!!!! lol, i thought it was funny!!!!!!!!!!!! (its ok if you didn’t) 🙂 happy halloween lol i didn’t really dress up like anything because I barely even have time to fully get ready in the morning, but if “a student who is heading over […]

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Color quantization using K-means clustering in ML.NET

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When I was looking for K-means use cases, I found out about Color quantization, a very interesting . I implemented it in Python and was wondering whether it would be as easy to implement in ML.NET. All the code is available in this GitHub repository. What is color quantization Color quantization is the usage of quantization, a lossy compression technique, in color spaces in order to reduce the number of unique colors in an image.

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A Simple Linear Regression

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Preliminaries Linear Algebra(the concepts of space, vector) Calculus An Introduction to Linear Regression Notations of Linear Regression1 We have already created a simple linear model in the post “An Introduction to Linear Regression”. According to the definition of linearity, we can develop the simplest linear regression model: [ Ysim w_1X+w_0tag{1} ] where the symbol (sim) is read as “is approximately modeled as”. Equation (1) can also be described as “regressing (Y) on (X)(or (Y) onto (X))”.

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An Introduction to Linear Regression

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Preliminariess Linear Algebra(the concepts of space, vector) Calculus What is Linear Regression Linear regression is a basic idea in statistical and machine learning based on the linear combination. And it was usually used to predict some responses to some inputs(predictors). Machine Learning and Statistical Learning Machine learning and statistical learning are similar but have some distinctions. In machine learning, models, regression models, or classification models, are used to predict the outputs of the new incoming inputs.

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Google Sign-In for ASP.NET Core Web APIs

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There is a lot of tutorials that show how to integrate Google Sign-In in your website, but only a handful show how to integrate it in a REST API. Today I’ll be showing how you can add Google Sign-In and still manage users in your back-end. Overview Here’s a sequence diagram showing how it all works:

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