Homework 1: Introduction to Machine Learning
Score: 8 = 7 (questions) + 0 (FAQ) + 1 (learning in public)
Homework URL: View submission
Machine Learning Zoomcamp 2025
Alfa Pradana
Total Score
148
Homework submissions
Homework 2: Machine Learning for Regression
Score: 10 = 5 (questions) + 0 (FAQ) + 5 (learning in public)
Homework URL: View submission
Learning in public links
- https://github.com/alfanugraha/mlzoomcamp-homework/blob/master/02_linear_regression_hw.ipynb
- https://colab.research.google.com/github/alfanugraha/mlzoomcamp-homework/blob/master/02_linear_regression_hw.ipynb
- https://www.kaggle.com/code/alfanugraha/02-linear-regression-hw
- https://x.com/alfanugraha/status/1975408778440052782?t=ng2hqSz22_ra6gJKq-WPRw&s=19
- https://alfanugraha.github.io/02_linear_regression.html
Homework 3: Machine Learning for Classification
Score: 11 = 6 (questions) + 0 (FAQ) + 5 (learning in public)
Homework URL: View submission
Learning in public links
- https://colab.research.google.com/github/alfanugraha/mlzoomcamp-homework/blob/master/03_classification_hw.ipynb
- https://alfanugraha.github.io/03_classification.html
- https://www.kaggle.com/code/alfanugraha/logistic-regression
- https://github.com/alfanugraha/mlzoomcamp-homework/blob/master/03_classification_hw.ipynb
- https://x.com/alfanugraha/status/1978344317212065955
Homework 4: Evaluation Metrics for Classification
Score: 11 = 6 (questions) + 0 (FAQ) + 5 (learning in public)
Homework URL: View submission
Learning in public links
- https://colab.research.google.com/github/alfanugraha/mlzoomcamp-homework/blob/master/04_evaluation_hw.ipynb
- https://www.kaggle.com/code/alfanugraha/evaluation
- https://alfanugraha.github.io/04_evaluation.html
- https://github.com/alfanugraha/mlzoomcamp-homework/blob/master/04_evaluation_hw.ipynb
- https://x.com/alfanugraha/status/1980769258591457470
Homework 5: Deploying Machine Learning Models
Score: 12 = 6 (questions) + 1 (FAQ) + 5 (learning in public)
Homework URL: View submission
Learning in public links
- https://github.com/alfanugraha/mlzoomcamp-homework/blob/master/hw05/05_deployment.ipynb
- https://colab.research.google.com/github/alfanugraha/mlzoomcamp-homework/blob/master/05_deployment.ipynb
- https://www.kaggle.com/code/alfanugraha/development
- https://alfanugraha.github.io/05_development.html
- https://x.com/alfanugraha/status/1985218763336425947
Homework 6: Decision Trees and Ensemble Learning
Score: 9 = 6 (questions) + 0 (FAQ) + 3 (learning in public)
Homework URL: View submission
Homework 8: Neural Networks and Deep Learning
Score: 8 = 5 (questions) + 0 (FAQ) + 3 (learning in public)
Homework URL: View submission
Homework 9: Serverless Deep Learning
Score: 11 = 6 (questions) + 0 (FAQ) + 5 (learning in public)
Homework URL: View submission
Learning in public links
- https://github.com/alfanugraha/mlzoomcamp-homework/blob/master/hw09/09_serverless_hw.ipynb
- https://colab.research.google.com/github/alfanugraha/mlzoomcamp-homework/blob/master/09_serverless_hw.ipynb
- https://x.com/alfanugraha/status/2002917040080994700?s=20
- https://alfanugraha.github.io/09_serverless.html
- https://www.kaggle.com/code/alfanugraha/serverless
Homework 10: Kubernetes
Score: 12 = 7 (questions) + 1 (FAQ) + 4 (learning in public)
Homework URL: View submission
Learning in public links
- https://github.com/alfanugraha/mlzoomcamp-homework/blob/master/10_kubernetes_hw.ipynb
- https://colab.research.google.com/github/alfanugraha/mlzoomcamp-homework/blob/master/10_kubernetes_hw.ipynb
- https://www.kaggle.com/code/alfanugraha/kubernetes
- https://x.com/alfanugraha/status/2005947552902877678?s=20
Only scored homework submissions appear here.
Project submissions
Midterm Project
PassedScore: 29 = 13 (project) + 9 (peer review) + 4 (learning in public / project) + 3 (learning in public / peer review) + 0 (FAQ)
Project URL: View project
Learning in public links
Capstone 2
PassedScore: 27 = 16 (project) + 9 (peer review) + 2 (learning in public / project) + 0 (learning in public / peer review) + 0 (FAQ)
Project URL: View project
Only completed project submissions appear here.