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所在平台: Udemy |
课程主页: https://www.udemy.com/course/machine-learning-in-r-image-classification-for-lulc-mapping/
课程评论：没有评论
课程名称：R语言中的机器学习：土地利用和地表覆盖图像分析 课程概述：欢迎参加本独特的Udemy课程，该课程专注于R和R-Studio中的机器学习，特别是用于土地利用和地表覆盖（LULC）图像分类！为何地理空间分析师（GIS、遥感）需要学习R？本课程是Udemy上的一项创新课程，为您提供了一种机会，以学习广受欢迎的R编程技能，用于基于遥感的机器学习分析。您将在课程中掌握的知识将使您能够在R中开展自己的机器学习图像数据分析。全球有超过200万名R用户，R在统计和数据科学领域的领先地位得到了巩固。每年R用户基数约增长40%，越来越多的组织依赖于R进行日常运营，选择今天报名参加该课程，您正在为自己的职业发展采取积极措施！ 课程亮点：该课程共分为7个部分，细致全面地涵盖机器学习的各个方面，包括理论和实践。您将会： - 掌握机器学习的扎实理论基础。 - 掌握用于图像分类的监督机器学习技术。 - 在R和R-Studio中应用机器学习算法（如随机森林和支持向量机）进行图像分类分析。 - 获得R编程的基本理解。 - 完全理解基于卫星图像分类的土地利用和地表覆盖（LULC）制图基础。 - 理解与LULC制图相关的遥感基础。 - 学习如何在QGIS中创建图像分类的训练和验证数据集。 - 建立基于机器学习的LULC分析图像分类模型并评估其稳健性。 - 在R中应用精度评估于机器学习基础的图像分类。 无需具备先前的R、统计学、机器学习或R知识：本课程将以全面介绍最重要的机器学习概念和技术作为起点。通过易于跟随的实用方法，我们将为您解密即使是最复杂的R编程概念，尤其是在卫星图像分析方面。您将在课程中使用来自不同提供商的真实图像数据（包括Landsat和Sentinel图像）来实施这些技术。因此，在完成这个R语言的机器学习课程后，您将具备处理不同数据流和数据科学包以在R中分析真实数据的技能。 课程特色：本课程通过提供实用、易于遵循的解决方案，旨在提升您的GIS和遥感技能以及R的熟练程度，从而与其他培训资源区分开来。您将能够为自己的项目启动空间数据分析，凭借先进的GIS能力、对最前沿机器学习算法的掌握及R编程的专业知识而获得未来雇主的认可。课程中包含实际练习，您将获得准确的指令、脚本和数据集，以使用R工具执行机器学习算法。 立即加入本课程，提升您的专业技能！
Mastering Machine Learning in R and R-Studio: Image Classification for Land Use and Land Cover (LULC) MappingWelcome to this unique Udemy course on Machine Learning in R and R-Studio, focusing on image classification for land use and land cover (LULC) mapping!Why Should Geospatial Analysts (GIS, Remote Sensing) Learn R?This course is a pioneering offering on Udemy, providing you with the opportunity to acquire highly sought-after R programming skills for Remote Sensing-based Machine Learning analysis in R.The knowledge you gain in this course will empower you to embark on your own Machine Learning image data analysis in R. With over 2 million R users worldwide, Oracle has solidified R's position as a leading programming language in statistics and data science. The R user base grows by approximately 40% each year, and an increasing number of organizations rely on it for their day-to-day operations. By enrolling in this course today, you are taking a proactive step to future-proof your career!Course Highlights:This comprehensive course comprises 7 sections, meticulously covering every aspect of Machine Learning, encompassing both theory and practice. You will:Gain a solid theoretical foundation in Machine Learning.Master supervised machine learning techniques for image classification.Apply machine learning algorithms (such as random forest and SVM) for image classification analysis in R and R-Studio.Acquire a fundamental understanding of R programming.Fully grasp the basics of Land Use and Land Cover (LULC) Mapping based on satellite image classification.Comprehend the fundamentals of Remote Sensing pertinent to LULC mapping.Learn how to create training and validation datasets for image classification in QGIS.Build machine learning-based image classification models for LULC analysis and evaluate their robustness in R.Apply accuracy assessment to Machine Learning-based image classification in R.No Prior R or Statistics/Machine Learning/R Knowledge Required:This course begins with a comprehensive introduction to the most essential Machine Learning concepts and techniques. I employ easy-to-follow, hands-on methods to demystify even the most intricate R programming concepts, especially in the context of satellite image analysis.Throughout the course, you will implement these techniques using real image data sourced from various providers, including Landsat and Sentinel images. As a result, upon completion of this Machine Learning course in R for image classification and LULC analysis, you will possess the skills to work with diverse data streams and data science packages to analyze real data in R.If this is your initial encounter with R, rest assured. This course serves as a comprehensive introduction to R and R programming.What Sets This Course Apart?This course distinguishes itself from other training resources by delivering practical, hands-on solutions in an easy-to-follow manner, aimed at enhancing your GIS and Remote Sensing skills, as well as your proficiency in R. You will be equipped to initiate spatial data analysis for your own projects, earning recognition from future employers for your advanced GIS capabilities, mastery of cutting-edge machine learning algorithms, and R programming proficiency.Integral to the course are practical exercises. You will receive precise instructions, scripts, and datasets to execute Machine Learning algorithms using R tools.Join This Course Now and Elevate Your Expertise!
