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CSE 158, CSE 258, DSC 256, MGTA 461 Web Mining and Recommender Systems, Fall 2023 : Assignment 2

CSE 158CSE 258DSC 256MGTA 461Web Mining and Recommender Systems

Identify a dataset to study, and perform an exploratory analysis of the data. Describe the dataset, including its basic statistics and properties, and report any interesting findings.

ENGN2912B Scientific Computing in C++ - Assignment 03: Prime Numbers, String and Expressions parser

ENGN2912BScientific Computing in C++Prime NumbersExpression ParserC++

This assignment contains two problems. First, we will implement a simple command-line application that calculates and displays prime numbers. Second, we will implement a `String` class capable of storing strings of variable lengths and use this class to write a function that parses mathematical expressions and computes their result.

MATH08068 Facets of Mathematics: Cubic Curves

MATH08068Facets of MathematicsCubic CurvesPython

For each question, you should provide explicit computations for solving the problems. Whenever appropriate, you should also provide theoretical justification for your results, quoting lemmas, theorems, etc from the lectures, tutorial worksheets and/or references

MATH4063 - SCIENTIFIC COMPUTING AND C++ Coursework 1: GMRES linear algebra solver

MATH4063SCIENTIFIC COMPUTING AND C++C++GMRESPDEGaussian Elimination

In this coursework you will build a 2D finite volume solver for the following PDE boundary value problem. In order to solve this problem, you will first define a sparse matrix structure, then write functions to apply the GMRES linear algebra solver and finally build and solve the linear system arising from the finite volume approximation

CS47100: Introduction to Artificial Intelligence - Assignment 3: Probability and Uncertainty, Bayesian Networks and Pacman

CS47100Introduction to Artificial IntelligencePythonProbability and UncertaintyBayesian NetworksPacman

In this assignment, we will use Pacman project 4. In project 4, you will design inference methods for Pacman agents to use to locate and eat invisible ghosts

COSC2500 Numerical Methods in Computational Science 2013 Projects

COSC2500Numerical Methods in Computational Sciencemathematical modelling

A typical project would involve the mathematical modelling of some system of interest, the numerical solution of the mathematical model, and discussion of the results (for example, what the results mean, comparison with experimental results, other computational results, and so on).

STAT3006/7305 Statistical Learning Assignment 4, 2023 High-Dimensional Analysis

STAT3006STAT7305Statistical LearningRStatistics

You should select one classifier for the task of classification, which you have not used in previous assignments. Probability-based classifiers discussed in this course include linear, quadratic, mixture and kernel density discriminant analysis.

STAT 361 Applied Methods in Statistics I (Fall 2023) Assignment 3: Linear regression

STAT 361Applied Methods in Statistics IRlinear regression

Consider the “Savings.txt” data posted. It is an economic dataset collected in 48 different countries. The variable “sr” is ratio of savings (aggregate personal saving divided by dis- posable income).

MATH36031 Problem Solving by Computer - Project 1: Vedic Multiply

The University of ManchesterMATH36031MatlabProblem Solving by Computer

In the tasks required for this project you are asked to use an algorithm which originates from the Vedic system of mathematics developed in India several hundred years ago. The algorithm is described in the video clip which is available via Blackboard in the Projects folder.

COSC2500 Numerical Methods in Computational Science - Assignment 3: Linear DEs

COSC2500Numerical Methods in Computational ScienceLinear DEsMatlabC

From Sauer computer problems 6.1: Using Euler’s method and a 4th-order Runge–Kutta method, solve the following IVPs on the interval [0, 1] where y(0) = 1 and

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