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- Learnings from Creator Camp Here are some thoughts after reflecting on my time at Creator Camp this past weekend.
- One day to day one For the past few weeks, I have been reflecting on this question: what stops me from turning one day into day one?
- UTMBCH25: perspective Let's figure out how intense this race actually is.
- Everesting and more Here's how I am going to make this year one of my most memorable.
- How to get started Here are the ways that work best for me to get started on a goal.
- UTMBCH25: day 0 It's been a while since I've done an athletic event that scared me. It's time.
- Have I made it? I used to think I'd be a tech entrepreneur CEO by the time I was thirty. Spoiler alert, that didn't happen.
- A new adventure I'm going to become a multisport endurance and adventure athlete.
- When is it time to quit? Quitting something isn't always necessarily a bad thing. Sometimes it's actually the best decision you can make.
- Dancing on quicksand I'm on the struggle bus; progress is slow and I'm questioning everything.
- Understanding the STOP dataset Here's a breakdown of the intents and slots for the Spoken Task-Oriented semantic Parsing (STOP) dataset.
- Spoken language understanding models I'm diving into spoken language understanding models for my research. What the heck are those? Let's find out.
- Cheat sheet: pyenv Here's a quick overview of using pyenv and pyenv-virtualenv.
- Python versions and virtual environments If you're working in the field of machine learning, it's only a matter of time before you run into Python dependency hell. Enter version managers and virtual environments.
- Focus: timers and such I used to think that timers wouldn't be useful to help me stay on task. Plot twist! I've incorporated them into my life and have found them incredible helpful to stay focused and increase productivity. Here's how I've started using them.
- There are no bad days Let me explain. I'll start with the point I'm trying to make: thinking you've had a bad day is ridiculous.
- Access to GPUs The first question you should be asking yourself is whether or not you actually need a GPU for what you're trying to accomplish. Let's assume you do. Here are some options I considered.
- Deep learning frameworks (PyTorch vs. TensorFlow) If you're searching for an in depth comparison of PyTorch and TensorFlow, this is not the post for you... there are numerous articles out there though! This post covers my high-level take on the two frameworks.
- The initial training pipeline It's not much, but hey, it's something and it's down on paper.
- Defining my master's research topic Where I find myself today is in the early stages of my fourth, yes fourth, attempt at defining and placing structure around my master's research project.
- How to get a master’s degree in 6 years (hopefully 🤞🏻) “Wait a minute, doesn’t a master’s take 2 years? Don’t they kick you out of the program after 5 years?” Well, yes and yes. My experience has been a little different though. Here’s how it’s gone.