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所在平台: Udemy |
课程主页: https://www.udemy.com/course/julia-programming-language/
课程评论：没有评论
Coursera 上的“Julia 编程用于机器学习”课程在线课程，旨在教授学员使用 Julia 语言进行问题解决，特别是在机器学习和数据科学领域。Julia 作为一种快速高效的科学计算编程语言，在本课程中将通过精心安排的主题和练习，帮助学员掌握其语法。 课程的重点之一是数据操作，这是数据分析的关键环节。学员将学习如何使用 Julia 的 DataFrame 和 TimeArray 对象进行数据处理。 整门课程包含四个项目，涵盖“数据分析”和基于回归分析的“机器学习模型构建”。通过这些项目，学员将学会使用 Julia 的相关包进行数据分析和机器学习。此外，课程还会介绍如何使用 Julia 的 StatsPlots 包进行数据可视化。 完成本课程后，学员将能够： * 熟练掌握 Julia 语法并能编写 Julia 程序。 * 运用多种数据类型和数据结构。 * 创建和操作数组。 * 处理原始文本。 * 定义函数和宏。 * 理解元编程概念。 * 创建自定义数据类型对象。 * 在 DataFrame 和 TimeArray 对象中进行数据操作。 * 构建用于数值预测的机器学习模型。 * 设置数据可视化工具。
Welcome to this online course on Julia! This course is for anyone who wants to learn Julia programming for problem solving. Machine learning and data science are the well applied domains of Julia programming. Above all, Julia is a fast and highly efficient programming language for scientific computation. Master Julia syntax for coding through arranged topics and exercises in this course.Full-fledged segment in this course is dedicated to know about core concept of data manipulation in Julia which is an essential part of data analysis.This course includes 4 projects on "data analysis" and for building "machine learning models based on regression analysis", to learn the usage of Julia packages for data analysis and machine learning.With data manipulation and building machine learning models, we will see the usage of Julia package StatsPlots for data visualization.By the end of this course, you will know how to work with Julia syntax for writing Julia program. working with several datatypes and data-structures. creating and manipulating arrays. working with raw text. defining functions and macros. metaprogramming. creating objects from new datatype that can be defined in Julia. data manipulation in DataFrame and TimeArray objects. building machine learning models for numeric prediction. setting up data visualization tools.See you inside the course!
