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CSC4005 Parallel Programming - Project 4 Parallel Programming with Machine Learning

CSC4005Parallel ProgrammingParallel Programming with Machine LearningC++

In this project, you will have the opportunity to gain insight and practice in using OpenACC to accelerate machine learning algorithms. Specifically, you will be accelerating softmax regression and neural networks (NNs).

COMP3611 Machine Learning - Assessment: Gaussian Distribution, PCA and Predict Cancer Mortality Rates in US counties

COMP3611Machine LearningGaussian DistributionPCAPredict Cancer Mortality Rates in US Countieslinear regression

Consider some continuous random variables generated from an unknown distribution stored in 'clean_data.npy'. Fit a univariate Gaussian distribution to this data and estimate the mean and variance of the Gaussian distribution using the maximum likelihood estimator.

6CCS3AIN Artificial Intelligence Reasoning and Decision Making - Coursework: Packman

6CCS3AINArtificial Intelligence Reasoning and Decision MakingPackmanMDP-solverPython

This coursework exercise asks you to write code to create an MDP-solver to work in the Pacman environment that we used for the practical exercises.

INT401: Fundamentals of Machine Learning Fall Semester Assignment 1: Feature Generation

INT401Fundamentals of Machine LearningFeature GenerationPython

Text categorization is the task on classifying a set of documents into categories from a set of predefined labels. Texts cannot be directly handled by our model

CS465/CS565: Introduction to Artificial Intelligence - Project 1: Search

CS465CS565Introduction to Artificial IntelligenceSearchPython

In this project, your Pacman agent will find paths through his maze world, both to reach a particular location and to collect food efficiently. You will build general search algorithms and apply them to Pacman scenarios.

CS465/CS565: Introduction to Artificial Intelligence - Project 3: Ghostbusters

CS465CS565Introduction to Artificial IntelligenceGhostbustersPython

Pacman spends his life running from ghosts, but things were not always so. Legend has it that many years ago, Pacman's great grandfather Grandpac learned to hunt ghosts for sport. However, he was blinded by his power and could only track ghosts by their banging and clanging.

CSCI-561 Foundations of Artificial Intelligence - Homework 3: Temporal Reasoning in Artificial Intelligence

CSCI-561CSCI561Foundations of Artificial IntelligenceTemporal ReasoningPythonPartially Observable Markov Decision Process

This homework explores the applications of Temporal Reasoning in Artificial Intelligence. In general, the solution for a temporal reasoning task involves taking a sequence of actions/observations on an Partially Observable Markov Decision Process (POMDP Environment)

DDA4210 Advanced Machine Learning - Assignment 1: Bias-variance decomposition, gradient boosting and recommendation systems

DDA4210Advanced Machine LearningBias-variance decompositiongradient boostingrecommendation systemsPCA

Derive the bias-variance decomposition for the squared error loss function. That is, show that for a model fS trained on a dataset S to predict a target y(x) for each x

CSC8112 Internet of Things Assessment 1: Machine learning-based IoT data processing pipeline

CSC8112Internet of ThingsPythondata injectorTime-series data predictionvisualization

Design a data injector component by leveraging Newcastle Urban Observatory IoT data streams

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