GOTO 2021 • How to Leverage Reinforcement Learning • Phil Winder & Rebecca Nugent

01:13:54 668 views 100% Published 3 weeks ago

This interview was recorded for the GOTO Book Club. #GOTOcon #GOTOBookClub

Phil Winder - Author of "Reinforcement Learning" & CEO of Winder Research
Rebecca Nugent - Stephen E. and Joyce Fienberg Professor of Statistics & Data Science at Carnegie Mellon University

Reinforcement learning (RL) focuses on sequential decision making and it is significantly different from machine learning. The recommendations based on RL algorithms could help you attain your business goals faster while also increasing engagement.
Join Phil Winder, Author of "Reinforcement Learning" and CEO of Winder Research, while he is talking with Rebecca Nugent, Fienberg Professor of Statistics & Data Science at Carnegie Mellon University, about key concepts from reinforcement learning and reveals the industry applications while also focusing on why some of the fundamentals like “ problem definition”, “how to get started with RL” and the switch in risk-taking from the management level to the engineering department while software is shaping the heart of the business.
The interview is based on Phil's book "Reinforcement Learning":

00:00 Intro
01:25 Introduction of Rebecca & Phil
01:57 Reinforcement learning (RL) vs machine learning (ML)
05:20 Key terminology for RL
12:44 RL in education
20:35 What kind of industry applications is RL best suited for?
26:19 Can we apply RL to long-term strategies?
30:49 Are the people running the algorithms, running the company?
35:54 RL and people
40:45 Problem definition and RL
44:35 The book
52:15 What excites you the most about RL?
55:18 What are the challenges with the interpretability of RL results?
01:04:54 Applying RL algorithms to real life
01:11:42 Thank you and goodbye Rebecca & Phil
01:12:55 Takeaways
01:13:35 Outro

Read the full transcription of the interview here:

Phil Winder • Reinforcement Learning •
#ReinforcementLearning #RL #AI #ML #Programming #ArtificialIntelligence #MachineLearning #DataScience #PhilWinder #RebeccaNugent #CarnegieMellon

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