Eva Sasson is a PyTN conference speaker presenting a talk on Identifying influencers via Slack Messages in Python using Network Analysis and NLP at PyTN 2019. We are thrilled to have Eva as a speaker, and share the enthusiasm for Python and PyTN 2019 below!
What have you been working on lately that you’re excited about? (It can totally be non-tech related!)
I’m excited to be starting up the “Sentry for Good” program at Sentry.io, a saas and open-source developer tool for error monitoring and remediation, where I’ve been working for the past year. The program offers sponsored support of our ‘cloud hosted Sentry’ to registered non-profits, edu, and other open-source tools, in addition to offering grants to developers in the open-source space. I’m driven and inspired by the impact that tech can have in the “real-world” and have seen a real need for non-profits and other charitable groups to leverage the power of existing technologies to advance their mission. The opportunity to utilize Sentry’s product to support communities in need has had been motivated (and super jazzed) this year.
What’s a way that you think the Python community has grown that you didn’t expect? Where do you think the Python community/ecosystem could develop further?
The biggest growth I’ve noticed in the Python community is the growth of libraries for data science! Statistics was historically computed in R. Now the packages that exist in Python are so powerful that (in my humble opinion) it surpasses what’s capabilities in R. Particularly, the ability to combine software engineering and data science for live data visualization. In the field of data science, I would like to see more attention given towards ethics in algorithms. There is growing attention towards this topic of how algorithms can learn bias, but I still believe we can be doing more to ensure that when we build models we don’t only look at accuracy but also make sure that our algorithms are fair and just if to be deployed in real-world situations.
What are some of the learning resources you’d suggest to newcomers to the Python language?
For Data Science, there are some great online courses on Udemy and Udacity, and for free and amazing videos, check out the YouTube channel Siraj Raval. Also, to test out and get practice, Kaggle is a great resource to practice building models and testing your accuracy! Great challenges on there to start with are the Iris dataset for predicting flower types and the Titanic dataset.
How hot do you like your hot chicken, and for how many meals are you going to eat it while you’re here?
I’m vegetarian, so no hot wings for me - but bring the heat for some hot veggies!
Do you have any advice for getting the most out of a technology conference?
Go to the talks that interest you, instead of the talks you “think you should be going to”. When you are interested in the material, you will be more engaged, and end up learning more than what you would get out of it if you were half paying attention (and playing on your phone) because you felt obligated to be there.
Additionally, say hi to the people sitting around you! Conferences are about meeting new and interesting people, just as much as they are about learning the content.
Have you ever been to Nashville? If so, is there anything you recommend first timers do while they’re here? If not, is there anything you’re excited to see or do while you’re here?
I visited Vanderbilt university for a weekend while I was in college, but still feel like a first-timer :). Outside of the conference and meeting some Tennessee Pythonistas (which I’m very excited about) I’m looking forward to checking out Nashville’s BlueGrass Music and craft beer.