Introduction to statistics Models Inference Examples MTHM501- Intro to Statistics Mark Kelson, Introduction to statistics Models Inference Examples Introduction to statistics Introduction to statistics Models Inference Examples INTRODUCTION Statistics is a tool that underpins the scientific method. The truth is beyond our grasp, but knowledge grows through the gathering of evidence. Concepts are applicable almost […]
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CS251: Cryptocurrencies and Blockchain Technologies Fall 2023 Programming Project #3 Ethereum Payment App Due: 11:59pm on Tuesday, Oct. 31, 2023 Submit via Gradescope (each answer on a separate page) code: 7DVJKY In this assignment, you’ll use Solidity and ethers.js to implement a complex decentralized ap- plication, or DApp, on Ethereum. You will write both a
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School of Computing: Assessment Brief Module title Blockchain Technologies Module code Assignment title Coursework Assignment type and description It is a programming assignment where students are re- quired to develop smart contracts for carpooling system. The aim of this assignment is to evaluate the students’ knowledge of blockchain based systems and smart con- tract development
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INFO1113 / COMP9003 Assignment Task Description In this assignment, you will create a game in the Java programming language using the Processing library for graphics and gradle as a dependency manager. In the game, players control tanks which can aim and fire at each other. Players gain score for hitting another player’s tank, causing them
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Task 2: Distributed Application and Dashboard The Distributed Application Your application must be of your own creative design. (We will use software similarity detection software to identify those who do not.) It can be simple, but should fetch information from a 3rd party source and do something of at least marginal value. For example, we
Analyzing and Visualizing Streaming Data with Kinesis Data Firehose, OpenSearch Service, and OpenSearch Dashboards Lab overview and objectives Big data problems often require solutions in real time. This is the velocity part of the five Vs of big data (volume, variety, velocity, veracity, and value). Common data sources for these scenarios include video streams, application
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Assignment 2 FIT5225 2023 SM1 CloudSnap: A Serverless Image Storage System with Tagging 1 Synopsis This assignment aims to build a cloud-based online system that allows users to store and retrieve images based on auto-generated tags. The focus of this project is to design a serverless application that enables clients to upload their images to
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CSC358: Principles of Computer Networking Programming Assignment 3: Proxy Server Due date: April 5, 11:59 PM The material is adapted from an assignment made by Dr. Larry Yueli Zhang, created with permission from Dr. Larry Yueli Zhang and Dr. Michael Liut. In this assignment, you will learn about proxy servers, a.k.a., web cache. Your task
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COMP90051 Statistical Machine Learning Project 1 Specification Due date: 8pm Thursday 25st April 2024 (competition closes 5pm) Melbourne timezone Weight: 25% Competition link: https://www.kaggle.com/t/b1b81f81dafe43c390b5bbff16ee2c8c 1 Overview Text generation has become an increasingly popular task with the rise of natural language processing (NLP) tech- niques and advancements in deep learning. Given a short text prompt written
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# Assessment 4 – ReactJS: BigBrain 1. Background & Motivation 2. The Task (Frontend) 3. The Support (Backend) 4. Constraints & Assumptions 5. Teamwork 6. Marking Criteria 7. Originality of Work 8. Submission 9. Late Submission Policy ## 0. Change Log * 02/04/2023: General edit clause added to 2.2.2 * 02/04/2023: Comments about advancing added
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