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Introduction
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Classroom Contents
Lukas Biewald on Founding Weights & Biases and FigureEight - Full Stack Deep Learning - March 2019
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- 1 Introduction
- 2 Lukass career
- 3 Hacker cred
- 4 AI is working
- 5 People making ludicrous predictions
- 6 Speech
- 7 Brands
- 8 CocaCola
- 9 Face Recognition
- 10 Blue River
- 11 Oxy
- 12 Personalized Medicine
- 13 Siobhans OS
- 14 Problems with FigureEight
- 15 Deep Learning vs ML
- 16 Space Odyssey
- 17 Netflix Prize
- 18 Selfdriving cars
- 19 Machine learning can be unpredictable
- 20 Puppy vs Bagel
- 21 Alphago
- 22 Tesla
- 23 Criminal Risk Scores
- 24 How to Inspect Systems
- 25 Adversarial Systems
- 26 Machine Learning Requires Training Data
- 27 Peter Norvig
- 28 Not hiring annotators
- 29 Cleaning your data
- 30 Data science joke
- 31 Andre Karpati
- 32 Lukass last compiler error
- 33 Why do we do it
- 34 Looking at more data
- 35 Realworld breakthroughs
- 36 Free datasets
- 37 Humans vs Computers
- 38 Design Patterns
- 39 Training
- 40 Human Loop System
- 41 Real Case Study
- 42 Better Tools Platforms
- 43 SageMakers
- 44 YouTube Channel
- 45 Medical Applications
- 46 FigureEight
- 47 ImageNet
- 48 Cancer Images
- 49 Microwave Oven
- 50 Selfdriving suitcase
- 51 How to ship deep learning projects
- 52 Contact Lukas Biewald
- 53 Lukas Biewald on Labeling
