COMP9417 – Machine Learning Homework 2: Classification models – Regularized Logistic Regression and the Perceptron Introduction In this homework we first look at a regularized version of logistic regression. You will im- plement the algorithm from scratch and compare it to the existing sklearn implementation. Special care will be taken to ensure that our implementation […]
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CS 6601 Artificial Intelligence Fall Semester 2022 Midterm Examination Paper Duration of Exam: 10 Oct 2022, 8:00 AM (EDT) – 17 Oct 2022, 8:00 AM (EDT) Weight: 15% No. pages: 35 No. Questions: 6 Total marks: 103 Instructions: • Before solving the exam, you should read the Ed post titled “Midterm Exam Next Week”. •
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CS 189 Introduction to Machine Learning Spring 2023 Jonathan Shewchuk HW4 Due: Friday, March 10 at 11:59 PM PST • Homework 4 consists of coding assignments and math problems. • We prefer that you typeset your answers using LATEX or other word processing software. If you haven’t yet learned LATEX, one of the crown jewels
Project 2: CS61Classify Part A Deadline: Thursday, February 16, 11:59:59 PM PT Part B Deadline: Thursday, March 2, 11:59:59 PM PT In this project, you will write RISC-V assembly code to classify handwritten digits with a simple machine learning algorithm. The goal of this project is to familiarize you with RISC-V, specifically calling convention, calling
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HackerRank Predict Financial Loss The Federal Reserve System is the central banking system of the United States of America. A bank failure occurs when a bank is unable to meet its obligations to its depositors or other creditors. They have kept a record of each failure of a commercial bank, savings association, and savings bank
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EECE5644 Fall 2018 – Exam 2 This assignment is due on Blackboard by 10:00am ET on Wednesday, December 5, 2018. Please submit your solutions on Blackboard in a single PDF file that includes all math, visual and quantitative results (plots, tables, etc), as well as your code (appended after your answers/solutions for each question). Do
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EECE5644 Introduction to Machine Learning and Pattern Recognition HW3 Question 1 (60%) In this exercise, you will train many multilayer perceptrons (MLPs) to approximate class label posteriors. The MLPs will be trained using maximum likelihood parameter estimation (or equiva- lently, minimum average cross-entropy loss). You will then use the trained models to approximate a maximum
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EECE5644 Introduction to Machine Learning and Pattern Recognition Assignment 2 Question 1 (50%) The probability density function (pdf) for a 2-dimensional real-valued random vector X is as follows: p(x) = p(L = 0)p(x|L = 0)+ p(L = 1)p(x|L = 1). Here L is the true class label that indicates which class-conditioned pdf generates the data.
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EECE5644 Spring 2023 – Assignment 1 Submit: Friday, 2023-February-17 before 08:00 ET (upload PDF to Canvas) Please submit your solutions in a single PDF file using the Canvas/Assignments page. The PDF should includes all math, numerical and visual results. Code can be appended in the PDF or a link to your online code repository can
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Homework Assignment 3: ML Ops::Spam Detection Due Date: 04/19 11:59pm In this assignment you will implement a machine learning model to predict whether a message is spam or not. Furthermore, you will create a system that upon receipt of an email message, it will automatically flag it as spam or not, based on the prediction
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