Arch Linux: Chromebook C720 Webcam Microphone Disappeared

After plugging in a third-party microphone, my laptop stopped detecting my webcam and microphone in its listed devices.

SSH: How to Set Up a Simple Local Media Server

While getting ready for my big move to Facebook, I came across way too many old laptops. One in particular had a solid 128GB of disk space that I couldn’t bring myself to throw into the electronics recycling bin. After looking around online for some good potential use cases, I finally decided that I’d try my hand at setting up a simple Linux-based local media server.

Pacman: File Conflicts

I got a Jupyter error: failed to commit transaction (conflicting files) while trying to update my packages.

Making an Arch Linux USB Flash Install Medium

I managed to mess up my USB installation medium tonight… managed to turn it into a NTFS, read-only USB, so I couldn’t delete anything.

Arch Linux: Post-Install Notes

Here’s some things you should do after successfully installing Arch Linux.

Binary Classification Metrics

Depending on the situation, the simple “number of correct classifications” error metric might not be the best metric to use in binary classification. Here, we explore several metrics and how they might be used for different problems.

Probabilitistic Classification

In binary classification problems, we have an input feature vector and we’d like to classify it into one of two classes. We did this by minimizing reasonable loss functions based on activation functions. In this very long post, we’ll take a probabilistic approach to classification and detail the generative framework.

Classification and Perceptron

We now leave the land of predicting real-numbered values to look at data classification. The discussion will conclude with one of the fundamental concepts behind classification, the Perceptron algorithm.

Linear Regression: Bayesian Approach, Normal Conjugacy

Understanding the linear regression from a probabilistic perspective allows us to perform more advanced statistical inference. Today, we’ll be applying Bayesian inference concepts to the linear regression. As a result, we’ll have a way to update the beliefs of our models as more data becomes accessible or account for prior knowledge when looking at data.

Nonlinearity: Basis Functions

We often work in linear space, but you might ask how we could capture nonlinearity? The answer lies in basis functions.

Model Selection

So far, we’ve looked at linear regression and K-Nearest Neighbors as potential models for estimating real-valued data. But how do we know which model is the best to use? In this post, we discuss overfitting, bias-variance decomposition, and regularization as factors when considering models.

Linear Regression: A Probabilistic Approach

Today, we look at the regression under a probabilistic modeling context that help us understand the reasons behind the least squares loss function.

Linear Regression: A Mathematical Approach

In this post, we’ll take a look at linear regression from a mathematical lens, ignoring the statistical interpretation. Here, we provide the derivation and interpretation of the closed form solution for the weights.

2017 Reflections: A Year of Curating

USW 30: Tangible Things was not the class I expected.

Introduction to Regression: K-Nearest Neighbors

Here, we’ll look at the K-Nearest Neighbors approach toward understanding one of the core ideas of machine learning, the regression.

Welcome to my Miscellaneous Blog!

Welcome to my miscellaneous blog! Here, you’ll find random things I’m thinking about or want to write about.

A Definitive Arch Linux Install Guide for the Chromebook C720

After the many, many times I’ve struggled to install and reinstall Arch Linux on a device, I’ve decided enough is enough. It’s time to write a complete guide for installing Arch on a Chromebook C720.

C4D: Fire Room BTS

My fall semester of senior year has come to an end! To celebrate, I fired up Cinema 4D to try and complete a video contest in a day or two. I gave up on the video contest, but at least I made this adorable Wes Anderson-esque interior. Let’s talk about some of the interesting bits.

C4D: Volume Effector

I recently tried out the Volume Effector in Cinema 4D. The tool allows for a discrete version of the boole operation, allowing for a pretty cool modular effect.

Algorithms: Maximum Sliding Window

The sliding window problem seeks to evaluate properties about every possible subarray without introducing a look-back penalty. In particular, the Maximum Sliding Window problem tries to find the maximum element in every contiguous fixed-length subarray.

Introduction to Inference: Coins and Discrete Probability

In data science, it all starts with a coin. Today, we’ll talk about the fundamentals of statistical inference for discrete models: how to determine the optimal parameters given data, how to incorporate prior knowledge, and how to make predictions. This assumes familiarity with random variables and the basics of probability theory.

C4D: Unreliable Booles

I came across an interesting issue while trying to displace the surface of an otherwise static object. When using the Boolean tool to intersect two objects with an animated displacement deformer, the point of intersection occasionally fails to render on certain frames.

Welcome to my Tech Blog!

Welcome to my tech blog! Here, you’ll find posts about the various things I’m working on as well as tips and insights I’ve gained during the project.

Welcome to my Problem Solving Blog!

Welcome to my problem solving blog! Here, you’ll find posts about interesting problems and riddles I’ve encountered as well as how I solved them.

Welcome to my Graphic Art Blog!

Welcome to my graphic art blog! Here, you’ll find posts about techniques I’ve discovered while creating and designing graphic art.

Welcome to my Data Science Blog!

Welcome to my data science blog! Here, you’ll find posts about the various things I’m working on as well as tips and insights I’ve gained during the project.