Homework 1: Introduction to Machine Learning

Score: 8 = 7 (questions) + 0 (FAQ) + 1 (learning in public)

Homework URL: View submission

Learning in public links: Show

• https://medium.com/@poojashreechoudhury7/my-machine-learning-journey-week-1-6f7eab150e0f

Homework 2: Machine Learning for Regression

Score: 8 = 5 (questions) + 0 (FAQ) + 3 (learning in public)

Homework URL: View submission

Learning in public links: Show

• https://medium.com/@poojashreechoudhury7/my-machine-learning-journey-week-2-regression-deep-dive-part-1-691479cac491
• https://medium.com/@poojashreechoudhury7/regression-part-2-easy-guide-22f3c43cf19c
• https://github.com/poojashree54/ML_ZoomCamp_Homework/blob/main/Regression/regression_hw.ipynb

Homework 3: Machine Learning for Classification

Score: 8 = 5 (questions) + 0 (FAQ) + 3 (learning in public)

Homework URL: View submission

Learning in public links: Show

• https://medium.com/@poojashreechoudhury7/logistic-regression-a-beginners-guide-to-classification-b2cf58bd70b9
• https://github.com/poojashree54/ML_ZoomCamp_Homework/blob/main/Classification/Classification_homework.ipynb
• https://www.kaggle.com/code/poojashreechoudhury/course-leadscore/notebook

Homework 4: Evaluation Metrics for Classification

Score: 10 = 6 (questions) + 0 (FAQ) + 4 (learning in public)

Homework URL: View submission

Learning in public links: Show

• https://www.kaggle.com/code/poojashreechoudhury/evaluation-hw
• https://github.com/poojashree54/ML_ZoomCamp_Homework/blob/main/evaluation/evaluation%20homework.ipynb
• https://medium.com/@poojashreechoudhury7/evaluating-logistic-regression-models-from-accuracy-to-auc-step-by-step-guide-b500ad78700a
• https://colab.research.google.com/drive/1lE6sGmy3eYVXpAnZiJ_huQ2_hBW4ZRQL?usp=sharing

Homework 5: Deploying Machine Learning Models

Score: 8 = 6 (questions) + 0 (FAQ) + 2 (learning in public)

Homework URL: View submission

Learning in public links: Show

• https://github.com/poojashree54/ML_ZoomCamp_Homework/tree/42f96b36e8c1541dad9b6627003585e7e1492954/deployment/deployment_hw
• https://medium.com/@poojashreechoudhury7/deploying-machine-learning-models-from-notebook-to-cloud-step-by-step-guide-fddedc1a0a7c

Homework 6: Decision Trees and Ensemble Learning

Score: 9 = 5 (questions) + 0 (FAQ) + 4 (learning in public)

Homework URL: View submission

Learning in public links: Show

• https://github.com/poojashree54/ML_ZoomCamp_Homework/blob/main/tree/tree%20hw.ipynb
• https://medium.com/@poojashreechoudhury7/building-a-credit-risk-scoring-model-with-decision-trees-step-by-step-ecc8094f4524
• https://colab.research.google.com/drive/1G72ZLyRRS5CVjdpB-IDUI9G2eFF0dlWR?usp=sharing
• https://www.kaggle.com/code/poojashreechoudhury/tree-homework

Homework 8: Neural Networks and Deep Learning

Score: 10 = 6 (questions) + 0 (FAQ) + 4 (learning in public)

Homework URL: View submission

Learning in public links: Show

• https://github.com/poojashree54/ML_ZoomCamp_Homework/blob/main/DL/dl-hw%20(1).ipynb
• https://www.kaggle.com/code/poojashreechoudhury/dl-hw
• https://medium.com/@poojashreechoudhury7/deep-learning-made-simple-from-images-to-predictions-step-by-step-guide-part-1-86cf59a88e09
• https://medium.com/@poojashreechoudhury7/deep-learning-made-simple-from-images-to-predictions-step-by-step-guide-part-2-53edc1a66823

Homework 9: Serverless Deep Learning

Score: 4 = 3 (questions) + 0 (FAQ) + 1 (learning in public)

Homework URL: View submission

Learning in public links: Show

• https://github.com/poojashree54/ML_ZoomCamp_Homework/blob/main/Serverless/Untitled.ipynb

Homework 10: Kubernetes

Score: 7 = 6 (questions) + 0 (FAQ) + 1 (learning in public)

Homework URL: View submission

Learning in public links: Show

• https://github.com/poojashree54/ML_ZoomCamp_Homework/blob/main/Kubernetes/Untitled.ipynb

Midterm Project

Project score: 14 Passed

Score: 25 = 14 (project) + 9 (peer review) + 2 (learning in public / project) + 0 (learning in public / peer review) + 0 (FAQ)

Project URL: View project

Learning in public links: Show

• https://medium.com/@poojashreechoudhury7/predicting-medical-insurance-costs-with-machine-learning-from-data-to-fastapi-deployment-98ea95671fd4
• https://github.com/poojashree54/Medical-Insurance-Cost-Prediction.git

Capstone 1

Project score: 14 Passed

Score: 25 = 14 (project) + 9 (peer review) + 2 (learning in public / project) + 0 (learning in public / peer review) + 0 (FAQ)

Project URL: View project

Learning in public links: Show

• https://github.com/poojashree54/Food-Calories-Prediction
• https://medium.com/@poojashreechoudhury7/building-an-indian-food-calorie-prediction-api-with-machine-learning-fastapi-docker-088d1f67ab6c