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G6061 Fundamentals of Machine Learning Assignment: Photo Classification
G6061Fundamentals of Machine LearningPhoto ClassificationImage ClassificationPythonCNN
The data come from photos, and your task is to come up with a machine learning method for classifying the photos according to whether their content is happy or sad. The data you are given for each photo consists of 3456 features. 3072 of these were extracted from a deep Convolutional Neural Network (CNN) [1], and the remaining 384 are gist features [2]. (You are given all these features as a 1-dimensional array, so you will not be performing any feature extraction on raw images.)
BUSANA7003 Business Analytics Project Final Project: AQR Asset Management
BUSANA7003Business AnalyticsAQR Asset ManagementPythonMachine Learning
You are starting a new job as a Business Analyst at AQR Asset Management, a global investment management firm focused on quantitative investment strategies. Your first task is to analyse the performance of US-listed securities during the COVID-19 market crash.
Project 3: Explore 1 of the given datasets: Breast Cancer, Global IQ Data and Natural Disasters
Data AnalysisMachine LearningR
In Week 9, briefings will be given by your tutors in your Lab class, and then a Video Briefing by your lecturer is in the first ten minutes of the Week 10 Lecture. See a guide to writing a nice report here Download here .
KIT317 Internet of Things and Artificial Intelligence - Assignment 3: Weather Prediction
KIT317KIT717Internet of Things and Artificial IntelligencePythonPHP
IoT devices collect data about the real world to help us make better decisions with that data. Raw data isn’t particularly helpful, so we analyse data to try it into more meaningful information. Sometimes we want to use this data not just to tell us about the past, but also to make inferences about the future.
Machine Learning in Practice Assignment: ML Solutions for Misinformation Detection in Social Media
Machine Learning in PracticePythonExplorationPreparationFeature GenerationClassification
Social media, particularly X (formally known as Twitter), has revolutionized the way information spreads, but it's also an incubator for fake news and misinformation. Misinformation on platform X can evolve from diverse forms and may stem from various sources, whether intentional or not, taking advantage of the platform's viral nature to widen its dissemination
Data 474: Final Project
Data ScienceMachine LearningStatistical LearningVisualizationRegressionClassification
Each team will identify a real data set for which there are interesting questions to answer by finding hidden pattern in data. Then different statistical learning approaches are applied to find the best way to answer these questions. Each team typically consists of 3 students. a team format is strongly encouraged.
Assignment 3: LDA Topic Modeling
LDATopic ModelingPython
LDA is a popular topic modeling algorithm widely used in the fields of Digital Humanities and Social Sciences. In the field of political communication, topic modeling is often applied for analyzing politicians Twitter/X posts, identitying thematic patterns or topics revolving around their posts
ACS341 Machine Learning Coursework Assignment: Household energy consumption
ACS341Machine LearningHousehold energy consumptionPythonPipeline
Accurately predicting household energy consumption allows local power distribution companies to better forecast energy trends and perform demand management1. Power system demand management has gained heightened importance as the world transitions towards renewable energy2
Project: Improving Classification through Self-supervised Learning
Self-supervised LearningClassificationPythonMelanoma Classification
While melanoma is the least common type of skin cancer, it tragically accounts for 75% of deaths from the disease, making it the deadliest form. Despite this, over 100,000 new cases of melanoma are expected in 2020, with nearly 7,000 people losing their lives to it. Just like with other cancers, early and accurate detection is crucial for effective treatment
COMP222 Principles of Computer Games Design and Implementation - Assignment 2: Design and Implement Artificial Intelligence for a Simplified PacMan game
COMP222Principles of Computer Games Design and ImplementationArtificial IntelligencePacManGame DevelopmentPython
Your tasks are to: • Design the AI for a simplified PacMan game, described below • Implement the AI that you designed in code (frameworks are provided for Python, Java). • Test and analyse how your AI performs
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