Python

You know that feeling when you solve a complex problem and everything just works? That’s exactly how I felt completing my latest knitting marathon. As someone who spends her days wrangling cloud infrastructure, I’ve discovered that knitting scratches the same problem-solving itch in surprisingly similar ways. Over the past few years, I’ve been treating knitting patterns like code repositories - each project a new challenge to debug, optimize, and deploy. And just like my home lab projects, some turn out better than others. Let me walk you through my recent “releases” and what I learned along the way. ...

When I set up my home lab with a Synology DS420j NAS, I wanted a project that would let me explore Claude’s API capabilities in a practical, everyday context. The result is a Python pipeline that takes photos from my NAS, hands them to Claude, and automatically generates and publishes a fully formatted blog post to my Hugo static site on GitHub. Here’s how I built it. The Hardware The foundation of this project is straightforward: a Synology DS420j — a 4-bay NAS — connected to a home router via a network switch. The NAS serves as the central storage layer, holding photos in a dedicated shared folder (blog/photos/latest/) that the pipeline reads from. The DS420j runs Synology’s DSM operating system and is accessible at a reserved local IP address, which makes it a reliable and addressable part of the home network. ...

In this post: Intro JSON File CSV File Python Script Writing the Python Script I was recently tasked with automating the replacement of key:value pairs in a JSON file. The goal was to take the output of a CLI command listing key:value pairs and place those keys/values in specific places within a JSON file. I decided to convert the output of the CLI command to a CSV file and have a python script use that CSV to create a new JSON file with updated keys/values. ...

Once you get past your first “Hello World” Python script, it’s good to learn how to use Python methods and classes. Methods and **functions **are a self-contained block of code that can be reused over and over. There are built-in functions that beginners in Python may already be familiar with, like print() and sum(). A user can also define a function (called a user-defined function) that executes a task they need done in their script multiple times. This is especially useful because it keeps the user from having to write that same chunk of code repeatedly. Variables that exist outside of the function can be passed to the function as parameters, but they are not required. The format of defining your own function is below: ...

Over the next year, I will be completing a research project exploring how biased training data effects the machine learning algorithm of self-driving cars. This project, which I’ll detail in a later post, involves deep neural networks (DNNs), computer vision, linear algebra, and more. Is this project a massive undertaking? Yes. Will that stop me? Absolutely not. Let’s get started. Neural Network Basics First, what is artificial intelligence (AI)? AI is a field of computer science pertaining to programming computers so that they demonstrate human-like intelligence. ...

In my first Capstone post I gave a rundown of basic AI terms and how to use Tensorflow to create your own machine learning (ML) script. I’m using Tensorflow to write a script that can process images of roads and determine whether there is an obstacle in the road or not. Since I’m studying self-driving cars, I’d like to see if using biased data to train an object detection script affects the model’s performance. To do this, I’m using a training dataset of clear, bright road images to train a neural network and then testing that script with corrupted images of roads. If the model can’t recognize obstacles in images that are corrupted, then the biased training dataset did have an affect on the model. ...