Challenges in Applying Machine Learning to Cybersecurity
I gave a talk called Challenges in Applying Machine Learning to Cybersecurity at BSides Asheville. Here are my slides:
And the video:
I gave a talk called Challenges in Applying Machine Learning to Cybersecurity at BSides Asheville. Here are my slides:
And the video:
A few years ago, I wrote a posted called https://tdhopper.com/how/. I recently gave a talk on the same topic at the Demystify Data Science Conference.
I gave a talk at the Data Science Conference on on building a realtime machine learning system with Kafka, Streamparse, and Storm. You can see the video on Youtube
I gave a talk last week at Research Triangle Analysts on understanding probabilistic topic models (specificly LDA) by using Python for simulation. Here’s the description:
Latent Dirichlet Allocation and related topic models are often presented in the form of complicated equations and confusing diagrams. Tim Hopper presents LDA as a generative model through probabilistic simulation in simple Python. Simulation will help data scientists to understand the model assumptions and limitations and more effectively use black box LDA implementations.
You can watch the video on Youtube:
I gave a talk at a recent Research Triangle Analysts meetup on Scikit-learn, the excellent machine learning libary for Python. The talk wasn’t recorded, but you can see the IPython notebook that I presented from.
I presented at INFORMS 2012 on Bringing Operations Research into the 21st Century with Online Video. You can see the recording on Youtube.