Elegant Northcutt

Homework 1: Introduction to Machine Learning

Score: 14 = 7 (questions) + 0 (FAQ) + 7 (learning in public)

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Homework 2: Machine Learning for Regression

Score: 13 = 6 (questions) + 0 (FAQ) + 7 (learning in public)

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Homework 3: Machine Learning for Classification

Score: 11 = 4 (questions) + 0 (FAQ) + 7 (learning in public)

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Homework 4: Evaluation Metrics for Classification

Score: 13 = 6 (questions) + 0 (FAQ) + 7 (learning in public)

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Homework 5: Deploying Machine Learning Models

Score: 13 = 6 (questions) + 0 (FAQ) + 7 (learning in public)

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Homework 6: Decision Trees and Ensemble Learning

Score: 13 = 6 (questions) + 0 (FAQ) + 7 (learning in public)

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Homework 8: Neural Networks and Deep Learning

Score: 11 = 4 (questions) + 0 (FAQ) + 7 (learning in public)

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Homework 9: Serverless Deep Learning

Score: 11 = 4 (questions) + 0 (FAQ) + 7 (learning in public)

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Score: 45 = 16 (project) + 9 (peer review) + 14 (learning in public / project) + 6 (learning in public / peer review) + 0 (FAQ)

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Score: 42 = 13 (project) + 9 (peer review) + 14 (learning in public / project) + 6 (learning in public / peer review) + 0 (FAQ)

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