Neural Nets

There’s a ton of excitement about reinforcement learning, a form of semi-supervised machine learning that underpins a lot of today’s cutting-edge artificial intelligence algorithms.  Here’s a crash course in the algorithmic machinery behind AlphaGo, and self-driving cars, and major logistical optimization projects—and the robots that, tomorrow, will clean our houses and (hopefully) not take over the world…

Reinforcement Learning for Artificial Intelligence

It's a funny thing to realize, but data science modeling is usually about either explainability, interpretation and understanding, or it's about predictive accuracy.  But usually not both--optimizing for one tends to compromise the other.   Leo Breiman was one of the titans of both kinds of modeling, a statistician who helped bring machine learning into statistics and vice versa.  In this episode, we unpack one of his seminal papers from 2001, when machine learning was just beginning to take root, and talk about how he made clear what machine learning could do for statistics and why it's so important.

Relevant links:
http://www.math.snu.ac.kr/~hichoi/machinelearning/(Breiman)%20Statistical%20Modeling--The%20Two%20Cultures.pdf

Two Cultures: Machine Learning and Statistics

In episode sixteen of season two, we get an introduction to Restricted Boltzmann Machines, we take a listener question about tuning hyperparameters,  plus we talk with Eric Lander of the Broad Institute. 

Eric Lander and Restricted Boltzmann Machines

What does it mean to steal a model?  It means someone (the thief, presumably) can re-create the predictions of the model without having access to the algorithm itself, or the training data.  Sound far-fetched?  It isn't.  If that person can ask for predictions from the model, and he (or she) asks just the right questions, the model can be reverse-engineered right out from under you.  

Relevant links:
https://www.usenix.org/system/files/conference/usenixsecurity16/sec16_paper_tramer.pdf

How to Steal a Model

Want another reason to be paranoid when using the free coffee shop wifi?  Allow us to introduce WindTalker, a system that cleverly combines a dose of signal processing with a dash of machine learning to (potentially) steal the PIN from your phone transactions without ever having physical access to your phone.  This episode has it all, folks--channel state information, ICMP echo requests, low-pass filtering, PCA, dynamic time warps, and the PIN for your phone.

Stealing a PIN with signal processing and machine learning

This week, we're doing a crash course in recurrent neural networks--what the structural pieces are that make a neural net recurrent, how that structure helps RNNs solve certain time series problems, and the importance of forgetfulness in RNNs.  

Relevant links: 
http://colah.github.io/posts/2015-08-Understanding-LSTMs/

Neural Nets

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