Jakob Johnson

Kailua Bay (Fujifilm X-S10, 18-55mm) A few weeks ago, I had the opportunity to present my research at MARC XIII in Kailua-Kona, HI. It’s the premier conference for nuclear forensics and nuclear chemistry. Since my work applies machine learning to nuclear forensics, it was a perfect venue to show off my work - and get to visit Hawai’i for the first time. Kamakanohu Beach and outrigger canoe (Fujifilm X-S10, 18-55mm) ...

Intro Much of this content will be based on the existing docs of Github Pages but with a bit more detailed steps. We’ll be using Jekyll in this, there are a number of other static website generators (such as Hugo), but since Pages has built in support for Jekyll, that’s where I’d recommend starting. Prerequisites You’ll need a GitHub account Ruby installed I’d recommend using RVM so as to not mess with your computer’s installation of Ruby [Optional] Your own domain name. Register one at a registrar like Namecheap. They’re pretty inexpensive, usually ~$10/year. They often also have deals on free or super cheap domains for students Note about Windows machines - I’d suggest setting up and using WSL for this. It will simplify installing things greatly. ...

Snowy Timber Top Mountain, Kolob Canyon Overlook (Fujifilm X-S10, 18-55mm) Since grade school I’ve gone to southern Utah over spring break. Usually it was hiking in Moab (before all the massive new hotels popped up). In recent years I’ve used it as a spring training camp of sorts, riding bikes in the St. George sun before the roads defrosted up north. ...

Most of the content here is from the Official Pytorch tutorial. I made this to be more concise and to present to a class. You can get the notebook here. PyTorch Background Data in PyTorch is stored in Tensors, which are almost identical to NumPy arrays. Their key differences are Auto gradient calculation (with torch.autograd) Ability to move to a GPU (with Tensor.to(device)) import torch data = [[1,2,3], [4,5,6], [7,8,9]] data_tensor = torch.tensor(data) print(data_tensor) tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) ones_tensor = torch.ones(size=data_tensor.shape, dtype=int) print(ones_tensor) # these tensors behave almost exactly like numpy arrays print(ones_tensor @ data_tensor) tensor([[1, 1, 1], [1, 1, 1], [1, 1, 1]]) tensor([[12, 15, 18], [12, 15, 18], [12, 15, 18]]) Datasets & DataLoaders Some datasets are available from Pytorch’s own libraries, such as MNIST or Fashion-MNIST ...

Why use Pyenv? Python virtual environments have been a useful way of managing python packages and package versions for quite a while. With vanilla Python, virtualenv is available, and for more complex cases Anaconda is a popular choice. Using these keeps your system installation of Python free of unnessecary clutter and packages as well as making it really easy to share dependencies with pip freeze. But what if some of the packages you wanted to install aren’t avaliable for your system’s installation of Python? Or what if your system is stuck on an old version of Python and you want to use the brand new shiny Python 3.13? That’s where pyenv comes in. It’s a series of shell ‘shims’ that seamlessly swap to different installations of Python. It’s frequently updated which means new versions of Python get added regularly so you can always stay up to date. Even better, since it’s simply shell commands you can install it without root access on your work machines! ...

Hello there! Welcome to my personal website and/or blog! This’ll be a place to post my random tutorials as well as some life blogging/travel photos. I like to take photos and this’ll be a fantastic place to post them! San Antonio Photos Here’s some photos I recently took while on a weekend trip to San Antonio TX to visit friends. Airplane at Salt Lake City Airport (Fujifilm X-S10, 18-55mm) ...