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Classroom Contents
Xavier Amatriain on Practical Deep Learning Systems - November 2019
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- 1 Introduction
- 2 Xaviers background
- 3 What is Qi
- 4 Publications
- 5 Lessons Learned
- 6 Question
- 7 Netflix Price
- 8 Meta Metadata
- 9 Unreasonable Effectiveness
- 10 Netflix example
- 11 Data
- 12 Transfer Learning
- 13 Fine Tuning
- 14 Simple Models
- 15 Occams Razor
- 16 More connections to deep learning
- 17 Recommended papers
- 18 Real life example
- 19 Complex models
- 20 Avoid this trap
- 21 Feature engineering
- 22 Reusable features
- 23 Examples
- 24 Architecture Engineering
- 25 Supervised vs Supervised
- 26 Models in Deep Learning
- 27 Self Supervision
- 28 Insample
- 29 Netflix Prize
- 30 Deep Models
- 31 Data Bias
- 32 Bias
- 33 Fairness
- 34 Models in Production
- 35 Models in Other Domains
- 36 Evaluation Approach
- 37 Metrics
- 38 Systems frameworks
- 39 Systems and frameworks
- 40 Machine learning infrastructure
- 41 Machine learning beyond deep learning
- 42 Deep learning vs linear models
- 43 Conclusions
- 44 Questions
