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Emphasizing data
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Classroom Contents
Celebrating Technology Leaders - Machine Learning Careers: Looking Beyond the Hype
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- 1 Introduction
- 2 Question
- 3 Nehas Story
- 4 PhD Myth
- 5 Hype vs Reality
- 6 Learning is not magic
- 7 Emphasizing data
- 8 Types of problems for ML
- 9 When to pick a good problem
- 10 Translating common sense into features
- 11 Industrial perspective
- 12 Chatbots
- 13 Opportunities and Challenges
- 14 Challenges
- 15 Challenges from academia
- 16 Opportunities
- 17 Audience Questions
- 18 Know Your Value
- 19 Have a Network Mindset
- 20 Improve Your Strengths
- 21 Audience Question
- 22 Making Tough Decisions
- 23 Bring Everyone Along
- 24 Take Responsibility
- 25 Netflix
- 26 Principles of Parsimony
- 27 Developing Features
- 28 Conferences
- 29 LinkedIn
- 30 Network
- 31 Github
- 32 Audience Feedback
- 33 Advice for Students
- 34 What Skills Do You Need
- 35 Final Thoughts
- 36 Advice
- 37 Final Advice
- 38 Keyword
