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Predicting Extreme Climate Behavior with Machine Learning · LearnSpace
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Predicting Extreme Climate Behavior with Machine Learning

Курс от University of Colorado Boulder
Средний≈ 24 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Throughout Predicting Extreme Climate Behavior with Machine Learning, you'll explore both theoretical concepts and practical applications or machine learning and data analysis. You'll begin by analyzing unsupervised learning algorithms, mastering techniques like clustering and dimensionality reduction, and applying them to real-world climate datasets. You'll also explore supervised learning, gaining hands-on experience with algorithms such as Logistic Regression, Decision Trees, and Neural Networks. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. The degree offers targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder

Навыки, которые вы освоите

Classification AlgorithmsSupervised LearningUnsupervised LearningDimensionality ReductionDecision Tree LearningLogistic RegressionRegression AnalysisMachine Learning MethodsMachine LearningArtificial Neural NetworksPredictive ModelingData ScienceApplied Machine LearningMachine Learning AlgorithmsStatistical Analysis

Программа курса

5 модулей · 59 учебных материалов

01Unsupervised Learning: Dimensionality Reduction14 материалов

Course Introduction

Course Updates and Accessibility SupportЧтениеEarn Academic Credit for your Work!ЧтениеCourse SupportЧтениеIntroduction to the CourseВидео

Учитесь у экспертов

Osita Onyejekwe

Assistant Professor

Predicting Extreme Climate Behavior with Machine Learning
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Обучение на Coursera

≈ 24 ч

5 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский, Казахский, Венгерский

Часть программы вашего университета
Meet the InstructorВидео
Introduction to Unsupervised Learning and TechniquesВидео
Unsupervised Learning and Climate AnomaliesОбсуждение

Principal Component Analysis

PCA OverviewВидеоPCA in Terms of SVDВидеоPrincipal Component Analysis for Extremes and Application to U.S. PrecipitationЧтениеPrincipal Component Analysis and Singular Value Decomposition (SVD) Задание

Module Assignment

PCA on Soil Temperature Data: Notebook WalkthroughВидеоPCA on Soil Temperature Data: Notebook WalkthroughЛабораторнаяPCA on Soil Moisture DataПрограммирование
02Unsupervised Learning: Clustering10 материалов

K-Means Clustering

Introduction to K-Means ClusteringВидеоK-Means Clustering MathematicalВидеоK-Means Clustering TheoreticalЧтениеK-Means Clustering ExtensionЧтениеK-Means ClusteringЗадание

Module Assignment

What is Clustering: Notebook WalkthroughВидеоWhat is Clustering: Notebook WalkthroughЛабораторнаяCluster AnalysisЧтениеClustering and Trend Analysis of Global Extreme Droughts from 1900 to 2014ЧтениеClusteringПрограммирование
03Supervised Learning: Regressions8 материалов

Linear Regression

Introduction to Statistical Regression: Notebook WalkthroughВидеоIntroduction to Statistical Regression: Notebook WalkthroughЛабораторнаяLinear RegressionЧтениеLinear RegressionЗадание

Linear and Multiple Linear Regression

Introduction to Multiple Linear Regression: Notebook WalkthroughВидеоIntroduction to Multiple Linear Regression: Notebook WalkthroughЛабораторнаяPrediction of Climate Variable using Multiple Linear RegressionЧтениеLinear and Multiple Linear RegressionПрограммирование
04Supervised Learning: Logistic Regression, Decision Trees, and SVMs17 материалов

Logistic Regression

Introduction to Logistic Regression: TheoreticalВидеоIntroduction to Logistic Regression: Notebook WalkthroughВидеоLogistic RegressionЧтениеLogistic RegressionПрограммирование

Decision Trees

Introduction to Decision Trees: TheoreticalВидеоIntroduction to Decision Trees: Practical Notebook WalkthroughВидеоIntroduction to Decision Trees: Practical Notebook WalkthroughЛабораторнаяDecision Trees and Random ForestsЧтениеDecision TreesПрограммирование

Support Vector Machines (SVMs)

Support Vector Machines: Part 1ВидеоSupport Vector Machines: Part 2ВидеоSupport Vector Machines: Part 3ВидеоSupport Vector Machines: Part 4ВидеоIntroduction to Support Vector Machines: Practical Notebook WalkthroughВидеоIntroduction to Support Vector Machines: Practical Notebook WalkthroughЛабораторная
05Supervised Learning: Neural Networks10 материалов

Introduction to Neural Networks: Part 1

Introduction to Neural Networks: Part 1ВидеоAn Introduction To and Applications of Neural NetworksЧтение

Introduction to Neural Networks: Part 2

Introduction to Neural Networks: Part 2ВидеоCharacterizing Drought Prediction With Deep LearningЧтениеNeural NetworksЗадание

Applying Neural Networks

Applying Neural Networks on Climate Data for Drought SeverityВидеоColorado Ground Water AnalysisЧтениеRepresentative Concentration Pathways (RCPs) RevisitedЧтениеNeural NetworksЛабораторнаяNeural NetworksОбсуждение
A Guide to Support Vector Machines and TutorialЧтение
Support Vector MachinesПрограммирование