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Project: Image Compression with K-Means Clustering

Project: Image Compression with K-Means Clustering

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9.2/10 (Our Score)
Product is rated as #20 in category Machine Learning

In this project, you will apply the k–means clustering unsupervised learning algorithm using scikit–learn and Python to build an image compression application with interactive controls. By the end of this 45–minute long project, you will be competent in pre–processing high–resolution image data for k–means clustering, conducting basic exploratory data analysis (EDA) and data visualization, applying a computationally time–efficient implementation of the k–means algorithm, Mini–Batch K–Means, to compress images, and leverage the Jupyter widgets library to build interactive GUI components to select images from a drop–down list and pick values of k using a slider. This course runs on Coursera’s hands–on project platform called Rhyme. On Rhyme, you do projects in a hands–on manner in your browser. You will get instant access to pre–configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and scikit–learn pre–installed. Notes: – You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. – This course …

Instructor Details

Snehan Kekre is a Machine Learning and Data Science Instructor at Rhyme. He will graduate in 2021 with a BSc in Computer Science and Artificial Intelligence from Minerva Schools at KGI, based in San Francisco. His interests include AI safety and alignment research. He believes that building a deep, technical understanding of machine learning and AI among students and engineers is necessary in order to grow the AI safety community. This passion drives him to design hands-on, project-based Machine Learning Courses on Rhyme.

Specification: Project: Image Compression with K-Means Clustering

Duration 4 hours
Year 2020
Level Beginner
Certificate Yes
Quizzes Yes

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Project: Image Compression with K-Means Clustering
Project: Image Compression with K-Means Clustering

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