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CS6601 Artificial Intelligence - Assignment 3: Bayes Nets
Artificial IntelligenceBayes NetsPythonProbabilistic ReasoningQuantifying UncertaintyMarkov Chain
In this assignment, you will work with probabilistic models known as Bayesian networks to efficiently calculate the answer to probability questions concerning discrete random variables.
Major Assignment 2: Probability & Hypothesis Testing Case Study
Probability & Hypothesis Testing Case StudyStatisticsHypothesis TestingProbability ModelingInferential Statistical Modeling
You are the manager of a well-established supermarket chain with multiple business operations, including a popular retail store and a factory that produces essential goods. As part of your role, you regularly analyse business data to make informed decisions and optimise performance, leveraging statistical tools and insights.
Random Number Generation: ICDF Method for Inhomogeneous Exponential Distribution
Random Number GenerationICDFInhomogeneous Exponential Distribution
The Inverse Cumulative Distribution Function (ICDF) method is a general technique for generating random numbers from any probability distribution for which the CDF (Cumulative Distribution Function) has a well-defined inverse. Here's how to apply the ICDF method to generate random numbers from an inhomogeneous exponential distribution:
Mathematics for Computer Science Project 2: PAs-Modeling and CSI-Prediction
Behavioral modelingCSI-PredictionNMSEPython
The project requires completing one of the following two tasks, and when submitting, include the project code and a report. Various methods such as non-linear regression or deep learning can be employed.
MTH208 NUMERICAL ANALYSIS - Coursework II: Approximating the absolute value function
MTH208NUMERICAL ANALYSISApproximating the absolute value function
The objective of this project is to explore and compare various numerical methods (interpolation with various basis or fitting in discrete and continuous cases) for approximating the absolute value function. You may provide basic ideas of each numerical method, give the implementation details and then compare their performance in terms of accuracy, implementation details and computational efficiency (You don’t need to include the code in the report).
STAT5002 Introduction to Statistics Assignment: Housing Price Analysis
STAT5002Introduction to StatisticsHousing Price AnalysisR
Using the data provided, choose one country and create an informative chart describing housing prices. You may choose the time period to draw data from as well as the country. You may explain the chart in no more than five sentences. What does it mean? What story does it tell about your chosen country and residential price?
MATH4063 Case Studies in Mathematical Modeling - Group Project: Jet Lag
MATH4063Case Studies in Mathematical ModelingJet LagThe Best HospitalBoarding and Disembarking a Plane
Organizing international meetings is not easy in many ways, including the problem that some of the participants may experience the effects of jet lag after recent travel from their home country to the meeting location which may be in a different time-zone, or in a different climate and time of year, and so on. All these things may dramatically affect the productivity of the meeting.
MATH1033 STATISTICS Coursework: Scottish Index of Multiple Deprivation
MATH1033STATISTICSRVisualization
The data file scottishData.csv contains a sample of the ”Indicator” data that were used to compute the 2020 Scottish Index of Multiple Deprivation (SIMD), a tool used by government bodies to support policy-making.
EEEN10036 C Programming Assignment: Escape From Island
EEEN10036C ProgrammingEscape From IslandC
The objective of this assignment is to write a C program which estimates the probability that an explorer will safely escape from a dinosaur- and volcano-infested island ("Jurassic Island") by taking random walks across it. As well as calculating the probability of escape, the mean and standard deviation of the path lengths should be determined for each starting cell.
MTHS2008 Advanced Mathematical Modelling for Process Engineers - COURSEWORK 2: DOUBLE NUMERICAL INTEGRATION AND FINITE
MTHS2008Advanced Mathematical Modelling for Process EngineersMathematical ModellingDOUBLE NUMERICAL INTEGRATIONPython
Using template_question_1a.py (on Moodle) as a template, write a module containing a function plot_region(a,b,y1,y2,n) to create a figure containing the plot of the region of integration for the double integral
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