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Introduction
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Classroom Contents
Machine Learning for Developers
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- 1 Introduction
- 2 The London Underground
- 3 Customer approach
- 4 What is ML
- 5 Learning from Data
- 6 Reinforced Learning
- 7 Regression
- 8 Validation
- 9 Overfitting
- 10 Regularization
- 11 Model Creation
- 12 The Problem
- 13 Demo
- 14 Cuddle
- 15 Users
- 16 Data
- 17 Splitting Data
- 18 Features Engineering
- 19 AWS Analytics Console
- 20 Input Variables
- 21 Fine Tuning
- 22 Creating a Model
- 23 Models
- 24 Deep Learning
- 25 Machine Imager
- 26 Graphical Processing
- 27 Using Machine Learning with Voice
- 28 Alexa
- 29 SDK
- 30 Defining Intents
- 31 Code
- 32 Create a skill
- 33 Realtime prediction
- 34 lambda function
- 35 weather API
- 36 calling the ML system
- 37 logging requests
- 38 language support
- 39 intents
- 40 sample utterance
- 41 configuration
- 42 HTTP endpoint
- 43 Lambda
- 44 Request
- 45 Service Response
- 46 Echo Sim
- 47 Recap
