Welcome to the "Machine Learning for Computer Vision" repository, your go-to hub for materials and resources for the KAIST CS492 course. Here, we offer a curated collection of coursework files, lab materials, and the course textbook, tailored to support your learning journey in exploring machine learning within the field of computer vision.
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Coursework: In this directory, discover the array of coursework files elucidating the assignments and projects undertaken by Team 19 during the Fall 2021 semester.
- CW1_Team_19.pdf: (Add a brief description of this document here)
- CW2_Team_19.pdf: (Add a brief description of this document here)
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Lab Materials: Explore a compilation of indispensable materials for Lab 2 and forthcoming labs, offering a step-by-step guide for each lab session.
- Lab2: (Add a brief description of this lab here)
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Textbook: The primary textbook for the course, facilitating a deep understanding of the pivotal concepts explored during the lectures.
- Richard O. Duda, Peter E. Hart, David G. Stork: Dive deep into the world of pattern classification through this essential text, ideal for every course participant.
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Fall21 Materials: A reservoir of all materials utilized during the Fall 2021 semester, aiming to be a priceless resource for both current and prospective students.
To make full use of the rich resources available in this repository, follow the step-by-step guide below:
- Clone the repository onto your local system using the command below:
git clone https://github.com/your-github-username/CS492-Machine-Learning-for-Computer-Vision.git