julia

Advent of Code 2021: A Julia Journal - Part 2

Advent of Code 2021: A Julia Journal - Part 2

Advent of Code is an advent calendar for programming puzzles. I decided to tackle this year’s set of 50 puzzles in Julia and journal my experiences along the way. I’m a beginner in Julia so I thought this would help me improve my skills. This post covers days 9 through 16. Day 9: Bracket matching Syntax error in navigation subsystem on line: all of them I over-engineered the heck out of this puzzle.
Advent of Code 2021: A Julia Journal - Part 1

Advent of Code 2021: A Julia Journal - Part 1

Advent of Code is an advent calendar for programming puzzles. I decided to tackle this year’s set of 50 puzzles in Julia and journal my experiences along the way. I’m a beginner in Julia so I thought this would help me improve my skills. This post covers days 1 through 8. All of my solutions are available on GitHub. Day 1: Increasing sequences Count the number of times a depth measurement increases from the previous measurement
Animated Unicode Plots with Julia

Animated Unicode Plots with Julia

I love Julia’s UnicodePlots.jl, a package for making pretty, colourful plots directly in the terminal. While playing around for Advent of Code I wrote a function to animate a sequence of Unicode plots. It’s not much, but I couldn’t find anything similar on Google so I thought I’d share. The move_up helper function is the fiddly part; it moves the cursor to the start of where the plot begins so that a new plot can be printed right on top.
Machine Learning Workflows with Julia

Machine Learning Workflows with Julia

I have a simple machine learning workflow that I recreate whenever I’m testing something new. I take some interesting data and a target, throw in some pre-processing, tune hyperparameters with cross-validation, and train a random forest. It’s all the basic ingredients for a machine learning model. Since I like Julia so much, I’ll recreate my simple machine learning workflow with Julia’s MLJ package. MLJ is like R’s parsnip, in that it unifies many machine learning packages with disparate APIs under a single syntactic umbrella.
First Impressions of Julia from an R User

First Impressions of Julia from an R User

It’s no secret that I love R and begrudgingly use Python. But there’s a another option for data science, and it promises the speed of C with the ease of use of R/Python. That language is Julia, and it’s a delight to use. I took some time to learn the basics, and I’m sharing my impressions here. Julia is not the most popular language in the world Before I go on, there’s one thing I want to stress here: Julia is not as popular as Python or R for doing stuff with data.