GOTO - The Brightest Minds in Tech

How to Leverage Reinforcement Learning • Phil Winder & Rebecca Nugent

Apr 15, 2021
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1
Introduction
00:00 • 4min
2
What Is Rear Reinforcement Learning?
04:22 • 3min
3
Learning to Ride a Bike
07:30 • 2min
4
What Is an MDP?
09:38 • 2min
5
Personalized Adaptive Learning Environments
12:08 • 5min
6
Could Retort Learning Be Adaptable?
16:54 • 3min
7
Is Machine Learning a Better Approach to Industry Applications?
19:47 • 4min
8
Machine Learning Versus Reinforcement Learning
24:08 • 3min
9
RL Framework
27:02 • 3min
10
Are You Taking on the Risk of Making Strategic Decisions?
29:38 • 5min
11
Data Science Experiential Learning
35:06 • 4min
12
The Importance of Problem Definition in Data Science
39:26 • 4min
13
The Reinforcement Learning Book Review
43:06 • 5min
14
Are You Just Brand New to Retort Learning?
47:51 • 2min
15
Getting Experience Playing With Models Is Really Important
49:53 • 2min
16
Is There a Future for ML?
51:27 • 3min
17
Is There Any Challenge With Interpretability of Reinforcement Learning?
54:03 • 5min
18
Data Science and Journalism
59:00 • 3min
19
How Can We Get More People to Work in This Space Without Having to Spend Years Learning All of the Technical Details?
01:01:57 • 2min
20
Sports Analytics Reactor Learning Example
01:03:38 • 5min
21
The Problem Isn't Telling the Player What to Do
01:08:24 • 4min