Isha Ponugoti

@iponugoti

Joined on Aug 31, 2023

  • <<< Back to main site <img src="https://hackmd.io/_uploads/H1NagEAT3.png" width=200> Due Date: 10/24/2024 Need help? Remember to check out Edstem and our website for TA help assistance. :::warningImportant Note: We will be grading all projects in Chrome. This means that you should check your finished project in Chrome before handing in. We will not be awarding credit if a task works in another browser but not Chrome. :::
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  • <<< Back to main site <img src="https://hackmd.io/_uploads/H1NagEAT3.png" width=200> Due Date: 11/2/2023 Need help? Remember to check out Edstem and our Website for TA help assistance. :::warningImportant Note: This lab has a longer background and introduction information. We recommend that you read through everything and refer back to it as you complete the tasks. :::
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  • Due Date: 11/20/2024 Need help? Remember to check out Edstem and our website for TA assistance. Assignment Overview Unsupervised learning involves finding hidden patterns or intrinsic structures in data. Unlike in supervised learning, there are no labeled responses. In this assignment, you will use foundational unsupervised learning techniques to develop an AI movie recommendation system. This assignment covers Principal Component Analysis (PCA), K-means clustering, and collaborative filtering--the heart of Netflix's movie recommendation algorithm. At the end of the assignment, you will compare collaborative filtering with and without clustering to see which method yields better recommendations. Introduction Last week, Steve introduced his friend Alex to the movie The Lion King. Alex loved it and is now eager for more recommendations. Steve decides to analyze his friends' watch data to recommend another movie Alex will love. In this assignment, you will help Steve achieve this by clustering similar movies together and recommending them based on other villagers' preferences. So grab your pickaxe, and let's dig into the data!
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