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 […]
EECE5644 2023 Spring Assignment 1 Read More »
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
COMS E6998 Cloud Computing and Big Data Assignment 3 Read More »
CS 189 / 289A Introduction to Machine Learning Fall 2022 Jennifer Listgarten, Jitendra Malik HW4 Due Tuesday 11/1 at 11:59pm • Homework 4 consists of written and programming questions. • 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
CS 189 / 289A Introduction to Machine Learning Read More »
CS 189 / 289 Introduction to Machine Learning Fall 2022 Jennifer Listgarten, Jitendra Malik HW1 Due 09/20/22 11:59 pm PT • Homework 1 consists of both written and coding questions. • 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
CS 189 / 289A Introduction to Machine Learning Fall 2022 Jennifer Listgarten, Jitendra Malik HW3 Due 10/14 at 11:59pm • Homework 3 consists only of written questions. • 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 of computer
CS 189 / 289A Introduction to Machine Learning Read More »
CS 189 / 289A Introduction to Machine Learning Fall 2022 Jennifer Listgarten, Jitendra Malik HW5 Due Tuesday 11/15 at 11:59pm • Homework 5 consists mainly of programming questions, with some written questions about the basics of the neural network architectures. • We prefer that you typeset your answers using LATEX or other word processing software.
CS 189 / 289A Introduction to Machine Learning Read More »
CS 189 / 289A Introduction to Machine Learning Fall 2022 Jennifer Listgarten, Jitendra Malik HW2 Due 10/04/21 at 11:59pm • Homework 2 consists entirely of coding questions. • 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 of computer
Data Analytics and Machine Learning Group Department of Informatics Technical University of Munich Ecorrection Place student sticker here Exam: Examiner: • Duringtheattendancecheckastickercontainingauniquecodewillbeputonthisexam. • Thiscodecontainsauniquenumberthatassociatesthisexamwithyourregistrationnumber. • This number is printed both next to the code and to the signature field in the attendance check list. Machine Learning IN2064 / Endterm Date: Thursday 13th February, 2020 Prof.
IN2064 Machine Learning exam Read More »
Data Analytics and Machine Learning Group Department of Informatics Technical University of Munich Place student sticker here Graded Exercise: Examiner: • Duringtheattendancecheckastickercontainingauniquecodewillbeputonthisexam. • Thiscodecontainsauniquenumberthatassociatesthisexamwithyourregistrationnumber. • Thisnumberisprintedbothnexttothecodeandtothesignaturefieldintheattendancechecklist. Machine Learning IN2064 / Endterm Date: Tuesday 16th February, 2021 Prof. Dr. ̈nnemann Time: 11:00 – 13:00 Working instructions • This graded exercise consists of 36 pages with a
CISC 271 Assignment #2 Regression and Cross-Validation The subject matter for this assignment is data of the environment, specifically air quality. The data were downloaded from the University of California at Irvine, which maintains extensive data sets for machine learning. The data were gently processed for use in this class. Coding for this requires multiple