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Advanced Methods in Machine Learning Applications · LearnSpace
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Advanced Methods in Machine Learning Applications

Курс от Johns Hopkins University
Средний≈ 20 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

The course "Advanced Methods in Machine Learning Applications" delves into sophisticated machine learning techniques, offering learners an in-depth understanding of ensemble learning, regression analysis, unsupervised learning, and reinforcement learning. The course emphasizes practical application, teaching students how to apply advanced techniques to solve complex problems and optimize model performance. Learners will explore methods like bagging, boosting, and stacking, as well as advanced regression approaches and clustering algorithms. What sets this course apart is its focus on real-world challenges, providing hands-on experience with advanced machine learning tools and techniques. From exploring reinforcement learning for decision-making to applying apriori analysis for association rule mining, this course equips learners with the skills to handle increasingly complex datasets and tasks. By the end of the course, learners will be able to implement, optimize, and evaluate sophisticated machine learning models, making them well-prepared to address advanced challenges in both research and industry.

Навыки, которые вы освоите

Reinforcement LearningDecision Tree LearningMachine Learning AlgorithmsLogistic RegressionPredictive ModelingRandom Forest AlgorithmUnsupervised LearningRegression AnalysisMachine Learning MethodsApplied Machine LearningClassification AlgorithmsMachine LearningModel OptimizationData MiningDimensionality ReductionModel Evaluation

Программа курса

5 модулей · 46 учебных материалов

01Course Introduction2 материалов
Course OverviewЧтениеInstructor Biography - Dr. Erhan GuvenЧтение
02Ensemble Learning10 материалов

Understanding Ensemble Learning

Ensemble Learning OverviewВидео

Учитесь у экспертов

Erhan Guven

Преподаватель курса

Advanced Methods in Machine Learning Applications
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Обучение на Coursera

≈ 20 ч

5 модулей

Язык: Английский

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

Часть программы вашего университета
Ensemble LearningВидео
Reading ReferencesЧтение
Understanding Ensemble LearningЗадание

Anatomy of Decision Tree Algorithms

Decision TreesВидеоDemonstrating the Power of Copious Weak LearnersВидеоReading ReferencesЧтениеAnatomy of Decision Tree AlgorithmsЗадание

Module-end Assessments

Ensemble LearningЗаданиеPractice Lab: Classification Using Ensemble Machine Learning TechniquesЛабораторная
03Regression11 материалов

Introduction to Regression Analysis

Regression OverviewВидеоLinear RegressionВидеоReading ReferencesЧтениеIntroduction to Regression AnalysisЗадание

Implementing Logistic Regression Classifiers

Logistic RegressionВидео Logistics Regression ClassifierВидеоReading ReferencesЧтениеImplementing Logistic Regression ClassifiersЗадание

Module-end Assessments

Self-Reflective Reading: Ground TruthЧтениеRegressionЗаданиеPractice Lab: Predictive Modeling Analysis Using Machine LearningЛабораторная
04Unsupervised Learning10 материалов

Clustering Algorithms in Unsupervised Learning

Unsupervised Learning OverviewВидеоUnsupervised LearningВидеоReading ReferencesЧтениеClustering Algorithms in Unsupervised LearningЗадание

Visualizing the Iris Dataset with Unsupervised Learning

Unsupervised Learning Worked ExampleВидеоUnsupervised Learning Visualizing Iris DatasetВидеоReading ReferencesЧтениеVisualizing the Iris Dataset with Unsupervised LearningЗадание

Module-end Assessments

Unsupervised LearningЗаданиеPractice Lab: Clustering AlgorithmsЛабораторная
05Reinforcement Learning and Apriori Analysis13 материалов

Understanding Reinforcement Learning Algorithms

Reinforcement Learning OverviewВидеоReinforcement LearningВидеоLearning the NIM GameВидеоReading ReferencesЧтениеUnderstanding Reinforcement Learning AlgorithmsЗадание

Setting Up the Apriori Algorithm in Weka

Apriori Analysis OverviewВидеоApriori AnalysisВидеоApriori Analysis Using Weka FrameworkВидеоReading ReferencesЧтениеSetting Up the Apriori Algorithm in WekaЗадание

Module-end Assessments

Self-Reflective Reading: Understanding Cluster Determination in Unsupervised LearningЧтениеReinforcement Learning and Apriori AnalysisЗаданиеGraded Lab: Exploring the NIM GameПрограммирование