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CS1026A Computer Science Fundamentals I - Assignment 3: YouTube Emotions

CS1026AComputer Science Fundamentals IPythonYouTube Emotions

Our goal in this assignment is to use a simplified version of the NRC Emotion Lexicon to classify YouTube comments based on one of the following emotions anger, joy, fear, trust, sadness, or anticipation. Based on the emotion contained in each comment for a particular video we then want to generate a report that details the most common emotions YouTube users have towards that video based on their comments.

ITD103 IT Systems Design - Assessment Task 3 - Design Challenge 2

ITD103IT Systems DesignUMLRequirements DeterminationFMCUse Case Diagram

This is a case-based assessment. Most of the tasks need to be completed based on the IT cases that have been provided in this document. We also have provided templates for your answers (available on Canvas). This assessment focuses on the analysis and design of the structure of an information system.

CS1315 Computer Programming Assignment One - Cheapest Payment

CS1315Computer ProgrammingC++

Your task is to find out the cheapest payment amount given the corresponding prices, discount settings and headcounts. The numbers are always in the valid range stated in page 1 (no checking is needed) but the numbers are not necessarily realistic

FIT5145: Foundations of Data Science Assignment 4: Shell Commands, Data Collection, Exploratory Data Analysis and Predictive Data Analysis

FIT5145Foundations of Data ScienceRData Analysis

In this task, you are required to explore and wrangle the data in the file “covid19-cable-broadcast.csv”, which contains transcript paragraphs that were collected from various programs aired in 2020 on cable and broadcast news networks, e.g., World News Tonight on ABC and Anderson Cooper 360 Degrees on CNN.

CSC3100 Data Structures Fall 2024 Programming - Assignment 2: Queue and Time Complexity

CSC3100Data StructuresQueueTime ComplexityJavaC++

Given an n-length list, the value ai in the list satisfies that ai ∈ {1, ..., n} and i = 1, ..., n. Then, numbering each element ai in the list as bi, bi = i. Please find the minimum number of elements that should be deleted so that the list of remaining elements has the same elements as the list of their corresponding numbers.

INFO1112 Computing 1B OS and Network Platforms - A1 - Just a friendly reminder

INFO1112Computing 1B OS and Network PlatformsPythonComputer NetworksOperating System

In this assignment, you'll be creating a basic application called "Jafr" (short for "Just a friendly reminder"). This application helps multiple users manage their tasks and meetings on a Unix-like OS

ECE4122/ECE6122 Advanced Programming Techniques for Engineering Applications - Lab 3: OpenGL with OBJ files and Multiple Objects

ECE4122ECE6122Advanced Programming Techniques for Engineering ApplicationsOpenGL3D graphicsC++

To create a dynamic 3D graphics application using lighting, shading, model transformations, and keyboard inputs.

MXB261 Modelling and Simulation Science - Assignment 2 - A Simulation Project - Modelling an Epidemic

MXB261Modelling and Simulation ScienceModelling an EpidemicLatin Hypercube SamplingMarkov ProcessMonte Carlo

The theme of this project is the effect of parameter values on the behaviour of a viral epidemic a mathematical model, in both a temporal and spatial setting.

COMS10016: Imperative and Functional Programming - Coursework 01: LIST CHALLENGE

COMS10016Imperative and Functional ProgrammingLIST CHALLENGEDoubly-linked ListsC

Before you start on this task make sure you watched and understood all lectures up to Lecture 15. You should have compiled, run, and understood all the code provided for pointers, dynamic data, stacks, and lists.

Assignment: Denoising Diffusion on Two-Pixel Images

Variational AutoencodersGenerative Adversarial NetworksDenoising DiffusionBeta SchedulingVariance EstimationDDPM

The field of image synthesis has evolved significantly in recent years. From auto-regressive models and Variational Autoencoders (VAEs) to Generative Adversarial Networks (GANs), we have now entered a new era of diffusion models. A key advantage of diffusion models over other generative approaches is their ability to avoid mode collapse, allowing them to produce a diverse range of images.