After working on a project all quarter long, it’s time to reflect on the progress that’s been made and what has been learned.

This tutorial will go over multiple machine learning models that will try to classify images. We will create models that will classify images as having a dog or a cat pictured in them, and analyze the models’ correctness.

Have you ever wanted to build a website from scratch? We will go over how to set up your own web app, including the use of databases, forms and CSS to make it nice and pretty.

This tutorial will explore webscraping using the Python package scrapy. We will be scraping the movie database IMDb with the goal of finding movies and TV shows that share the same actors from any given show or movie.

We will be working with data from a multitude of different weather stations from around the world that have kept track of the average temperature per month for many years. We will be using this data to answer a few questions.

In this tutorial, we will learn how to use the pandas, seaborn and matplotlib.pyplot packages to manipulate data and present a simple data visualization with the Palmer Penguins data set.

In this post, we’ll get set up with Jekyll. Jekyll is a static site converter, which you can use to turn plaintext documents into attractive webpages.

It is possible to construct, maintain, and update your blog fully from GitHub. In this case, it is not necessary to download your blog’s files or modify them on your computer. However, when constructing complex posts involving code and figures, local editing can be more comfortable. Additionally, since GitHub Pages usually takes a few minutes to publish all your changes, modifying your blog locally allows you to more quickly see the results of your changes, including errors when they arise. In this post, I’ll show how to manage your blog locally.