Edison Marcelo

Homework 2: Machine Learning for Regression

Score: 12 = 5 (questions) + 1 (FAQ) + 6 (learning in public)

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Homework 3: Machine Learning for Classification

Score: 14 = 6 (questions) + 1 (FAQ) + 7 (learning in public)

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Homework 4: Evaluation Metrics for Classification

Score: 14 = 6 (questions) + 1 (FAQ) + 7 (learning in public)

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Homework 5: Deploying Machine Learning Models

Score: 14 = 6 (questions) + 1 (FAQ) + 7 (learning in public)

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Homework 6: Decision Trees and Ensemble Learning

Score: 14 = 6 (questions) + 1 (FAQ) + 7 (learning in public)

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Homework 8: Neural Networks and Deep Learning

Score: 14 = 6 (questions) + 1 (FAQ) + 7 (learning in public)

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Homework 9: Serverless Deep Learning

Score: 14 = 6 (questions) + 1 (FAQ) + 7 (learning in public)

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Homework 10: Kubernetes and TensorFlow Serving

Score: 15 = 7 (questions) + 1 (FAQ) + 7 (learning in public)

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ML Zoomcamp 2024 Competition

Score: 26 = 19 (questions) + 0 (FAQ) + 7 (learning in public)

Article

Score: 27 = 20 (questions) + 0 (FAQ) + 7 (learning in public)

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Score: 44 = 14 (project) + 9 (peer review) + 14 (learning in public / project) + 6 (learning in public / peer review) + 1 (FAQ)

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Score: 45 = 15 (project) + 9 (peer review) + 14 (learning in public / project) + 6 (learning in public / peer review) + 1 (FAQ)

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