Julia Tutorial Julia Tutorial In this Julia Tutorial, we will learn how to install Julia in your machine, write a simple Julia program, walk through the packages available in Julia, a typical Julia program for data analytics, and some of the use cases that call for Julia programming. What is Julia Julia is a high-level programming language. Julia is designed to address high-performance numerical analysis. It is as fast as C and as high-level as Python. So Julia is a ...
CS/ECE/ISyE 524 Introduction to Optimization Spring 2017–18 Julia tutorial Introduction Some useful pointers Getting started Julia syntax Plots in Julia Learning JuMP Submitting a notebook Laurent Lessard (www.laurentlessard.com) Why this tutorial? To give you the resources and tools necessary to learn Julia, IJulia, and JuMP quickly and eciently. Most of the learning will happen on your own as you work on homework assignments and the project The goal of this tutorial is to make that learning easy ...
TF 502 SIST, ShanghaiTech JULIA-Tutorial 2: Polynomial Interpolation Introduction Implementation of Divided Dierences Implementation of Horner’s algorithm Testing and Debugging Boris Houska 2-1 Contents Introduction Implementation of Divided Dierences Implementation of Horner’s algorithm Testing and Debugging JULIA-Tutorial 2: Polynomial Interpolation 2-2 Objectives In this tutorial we will learn how to implement a simple polynomial interpolation tool in JULIA by using divided dierences. JULIA-Tutorial 2: Polynomial Interpolation 2-3 Programming Guidelines Try to keep the following general programming guidelines in ...
Julia Tutorial Set Up Instructions No prior installation is required for this Intro to Julia tutorial, as you will have the option to run all workshop materials from remotely hosted Jupyter notebooks at JuliaBox.com. However, you may prefer to install and run Julia locally. We suggest you try out JuliaBox prior to the tutorial to decide which option is better for you! JuliaBox Prior to the tutorial, please go to JuliaBox.com and sign in with Google, LinkedIn, or ...
Chapter 1 Julia Tutorial 1.1 WhyJulia? Juliaisamodern,expressive,high-performanceprogramminglanguagedesignedforscientic computation and data manipulation. Originally developed by a group of computer scientists and mathematicians at MIT led by Alan Edelman, Julia combines three key features for highly intensive computing tasks as perhaps no other contemporary programming language does: it is fast, easy to learn and use, and open source. Among its competitors, C/C++ is extremely fast and the open-source compilers available for it are excellent, but it is hard to ...
Julia Programming 1 Julia Programming About the Tutorial One of the facts about scientific programming is that it requires high performance flexible dynamic programming language. Unfortunately, to a great extent, the domain experts have moved to slower dynamic programming languages. There can be many good reasons for using such dynamic programming languages and, in fact, their use cannot be diminished as well. On the flip side, what can we expect from modern language design and compiler techniques? Some of the ...
Rotating Rasters and Age-Based Masking of Raster Data Authors: Christian Heine & Kara J. Matthews Edited by: Julia Sheehan EarthByte Research Group, School of Geosciences, The University of Sydney, Australia Rotating rasters and age-based masking of Raster data Background Included Files Exercise 1: Rotating and cookie cutting raster data Exercise 2: Age -based masking or raster data Appendix Background GPlates 1.5 includes the functionality to apply age-based masking of raster data. This means any age-grid can be ...
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