Georgia Institute of Technology CS 6601 Artificial Intelligence Final Exam Spring 2025 Duration of Exam: April 24th 2025, 8:00 AM (EDT) – May 1st 2025, 7:59 AM (EDT) Weight: 20% Points: 100 + 5 Extra Credit Submission: Via Canvas. Unlimited attempts during exam window, only last submission will be used for grading. Instructions IMPORTANT*: Please […]
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CS 188 Spring 2025 Projects / Project5 Project 5: Machine Learning Due: Fri Apr 25. TABLE OF CONTENTS Introduction Installation Installing Pytorch Possible Numpy Bug: If you get any numpy errors, try downgrading to numpy version 1.24.3 or any version < 2.0.0. Pytorch Provided Functions (Part I) Question 1 (6 points): Neural Network Tips Building
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Take-Home Final Exam for ISyE 7406 This is an open-book take-home final exam. You are free to use any recourses including textbooks, notes, computers and internet, but no collaborations are allowed, particularly you cannot commu- nicate, online or orally, with any other people about this midterm (except the TAs or instructor via piazza if you
FIT5003 Software Security Assignment 3 (S2 2024) Total Marks 100 Please Check Moodle for the Due Date 1 Overview The learning objective of this assignment is for you to perform penetration testing, thread modelling, and write ethics for hacking. The lab setup employed in Lab10 (Penetration Testing) can be utilized for this assignment. 2 Submission
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Assessment 2 Weighting: 45% Total marks: 40 The assessment covers the content of Week 3-6. It addresses the following learning outcome(s): • Analyse real world tasks using multi-layer perceptron neural network, ARMA/ARIMA and LSTM for classiIication and time-series prediction. • Develop and deploy multi-layer perceptron neural network, ARMA/ARIMA and LSTM in Python • Tune hyperparameters
CS/ECE/STAT-861: Theoretical Foundations of Machine Learning University of Wisconsin–Madison, Fall 2023 Homework 2. Due 10/27/2023, 11.00 am Instructions: 1. Homework is due at 11 am on the due date. Please hand over your homework at the beginning of class. Please see the course website for the policy on late submission. 2. I recommend that you
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CS/ECE/STAT-861: Theoretical Foundations of Machine Learning University of Wisconsin–Madison, Fall 2023 Homework 0. Due 9/15/2023, 11.00 am Instructions: 1. Homework is due at 11 am on the due date. Please hand over your homework at the beginning of class. Please see the course website for the policy on late submission. 2. I recommend that you
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CS/ECE/STAT-861: Theoretical Foundations of Machine Learning University of Wisconsin–Madison, Fall 2023 Homework 1. Due 10/06/2023, 11.00 am Instructions: 1. Homework is due at 11 am on the due date. Please hand over your homework at the beginning of class. Please see the course website for the policy on late submission. 2. I recommend that you
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CS/ECE/STAT-861: Theoretical Foundations of Machine Learning University of Wisconsin–Madison, Fall 2023 Homework 3. Due 11/08/2023, 11.00 am Instructions: 1. Homework is due at 11 am on the due date. Please hand over your homework at the beginning of class. Please see the course website for the policy on late submissions. 2. I recommend that you
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CS861: Theoretical Foundations of Machine Learning Lecture 5 – 09/15/2023 University of Wisconsin–Madison, Fall 2023 Lecture 05: Growth Function and VC Dimension Lecturer: Kirthevasan Kandasamy Scribed by: Chenghui Zheng, Yixuan Zhang Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only with
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