Interpreting Machine Learning Models

Find out how to better explain the results of your machine learning models to maximize the impact of your work.

March 28, 2018 | 10:00 - 11:00 a.m. PST

About the webinar

Machine learning has come a long way since it first emerged in academia. Now, it's helping industries across the globe automate solutions to real-world problems, like retaining customers with personalized product recommendations or detecting anomalies such as network intrusion and fraud. Despite these advances, machine learning algorithms are still perceived as alchemy by those working closely with their outputs — and because these "black box" models are so little understood, their fairness, accountability, and transparency often come into question.

In this live webinar, O'Reilly Media Learning Group Director Paco Nathan and University of California, Irvine Assistant Professor of Computer Science Sameer Singh will join Lead Data Scientist Pramit Choudhary to discuss the need for methods that make the process of explaining machine learning models more intuitive. They will also be evaluating myths about model interpretability, from both research and business perspectives.

  • Date: Tuesday, March 28, 2018

  • Time: 10:00 - 11:00 a.m. PST

Register for the event

Paco Nathan
Director of Learning Group, O'Reilly Media

Paco Nathan is the Director of Learning Group at O’Reilly Media. He has over 35 years of experience in the technology industry, ranging from Bell Labs to early-stage startups. He is also known as a "player/coach," with core expertise in data science, natural language processing, machine learning, distributed systems, and cloud computing. He was cited as one of the Top 30 People in Big Data and Analytics by Innovation Enterprise in 2015, and is an advisor for Amplify Partners.

Sameer Singh
Assistant Professor of Computer Science, University of California, Irvine

Dr. Sameer Singh is an Assistant Professor of Computer Science at the University of California, Irvine. He applies large-scale and interpretable machine learning to natural language processing. Before UCI, Sameer was a Postdoctoral Research Associate at the University of Washington, and received his PhD from University of Massachusetts, Amherst.

Pramit Choudhary
Lead Data Scientist,
Pramit Choudhary is a Lead Data Scientist at He enjoys applying and optimizing classical machine learning algorithms and Bayesian design strategy to solve real-world problems. Currently, he is exploring better ways to extract, evaluate, and explain a model’s learned decision policies in a human understandable way. Before joining, he used machine learning algorithms to help eHarmony users find love.