Meet Amelia Taylor: Robots, Biology and Unsupervised Model Selection
This post is part of a series introducing the speakers at the PyBay2018 conference in San Francisco later this month. It’s a great chance to learn and connect with an engaged and diverse community of Python developers. We hope you’ll join us!
What are you going to be speaking about at PyBay 2018, and why are you excited to give this talk?
I will present an end-to-end approach, in python, for model selection with an emphasis on parameter tuning unsupervised outlier detection algorithms. The problem of model selection and tuning parameters is well studied for supervised and even semi-supervised (labels are human evaluation) anomaly and outlier detection algorithms, but there are few resources readily available in the unsupervised arena and I’m excited to share my approach to this problem. I’m also really excited about giving my first talk since I left academia to become a data scientist.
How did you get into programming and Python?
I started programming when I was a young kid and my parents brought home our first computer, a Bell & Howell where we plugged in an old TV and used a tape recorder for storing simple programs. My mom and I learned to program that computer together. Recently, I decided to pursue a second career as a data scientist after many years as a mathematics professor and taught myself python so I could do production level data products.
What’s one of the features about Python you like the best?
I like that there is often more than one way to solve a problem in Python, particularly with Pandas. I appreciate this makes python sometimes a little problematic, but for me it opens up the door to creative problem solving, quick prototypes and [the] enjoyment of finding and learning more efficient and elegant ways to solve a problem.
What’s your favorite Python library (core or third-party), and why?
I love Jupyter lab. I’m particularly enjoying, for the work I do, the ease with which I can have a notebook open next to a working module or function file. This is really speeding up my transition from experimental data product to full production.
What can you be found doing when you’re not writing code?
Mostly trail running or mountain biking. This fall, just after PyBay I’m going to run the Wonderland Trail around Mt. Rainier in 3 days with my husband. To train for that I’m running up mountains all over Washington and Oregon.
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