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Classroom Contents
When to Use Machine Learning - Tips, Tricks and Warnings
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- 1 Intro
- 2 Who am I
- 3 Open source projects
- 4 Machine learning
- 5 Decision trees
- 6 Predicting spam
- 7 Bait logic
- 8 significance of machine learning
- 9 how I came to this idea
- 10 example data
- 11 main takeaway
- 12 another example
- 13 x2y problems
- 14 ImageNet
- 15 Insurance
- 16 Academic Data
- 17 Localisation
- 18 Transfer Learning
- 19 Image Data
- 20 Compliance
- 21 Neural Network
- 22 Cryptocurrency
- 23 Connecting to ML
- 24 Python for ML
- 25 X2Y
- 26 Reading the data
- 27 Bundle Preprocessing
- 28 In the end
- 29 Questions
