Keynote - Julia Evans: How you can trick a neural network
Details
Rust + nix: unix systems programming made safe and fun - Kamal Marhubi
Systems programming often seems scary. To start with, you need to know C. Debugging obscure pointer issues is hard, and nobody will tell you if you're passing the wrong type of flag to a function. Kamal has been doing a bunch of systems programming in Rust recently, and he's found it a lot easier, more accessible, and more fun.
You (yes, you!) can trick a neural network: moving away from black-box machine learning - Julia Evans, Machine Learning @ Stripe
There's a neural network you can download for free (GoogLeNet) that's better at recognizing dog breeds than I am. It's extremely good. We're going to intentionally convince it that a panda is a ferret or a fox, a black screen is a piece of velvet, and all kinds of other strange things. Then I'll talk a little more broadly about how treating machine learning as a black box means you can't break, understand, or debug it. You'll come away understanding a little better what flaws in a machine learning model might look like, how to find them, and why it's important. No prior knowledge of neural networks or machine learning wizardry required.
About the Speakers:
Julia Evans (@b0Rk (https://twitter.com/b0rk))
Julia is currently a Machine Learning Engineer at Stripe. She likes playing with data and making Serious Systems do silly things. Julia spends a lot of my time giving talks and organizing events for women who {like to, would like to} program. Read Julia's blog here (http://jvns.ca).
Kamal Marhubi (@kamalmarhubi (https://twitter.com/kamalmarhubi))
Kamal Marhubi is a polyglot programmer who lives in Montréal. He is not-so-secretly addicted to English change-ringing, and has rung the bells of over twenty churches in England, Canada, and the US.
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