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Intermediate Data Manipulation and Machine Learning · LearnSpace
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Intermediate Data Manipulation and Machine Learning

Курс от Packt
Средний≈ 16.8 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this comprehensive course, you will explore artificial intelligence (AI) and its core concepts, forming a solid foundation for machine learning. You will delve into regression analysis, applying univariate, polynomial, and multivariate regression techniques to real-world problems through interactive labs. Next, you will learn model preparation and evaluation, focusing on underfitting, overfitting, data splitting, and resampling methods, alongside regularization techniques to enhance model performance. The course covers classification methods, including confusion matrices, ROC curves, decision trees, random forests, logistic regression, and support vector machines, all paired with practical labs. You will also explore ensemble models and association rules, like the Apriori algorithm, to uncover hidden data patterns. Designed for data scientists, machine learning enthusiasts, and technical professionals, this course requires a basic understanding of machine learning concepts and Python programming. Learning outcomes include grasping AI and machine learning fundamentals, applying regression analysis, building and evaluating models, implementing classification techniques, performing clustering and dimensionality reduction, uncovering patterns with association rules, and applying reinforcement learning principles.

Навыки, которые вы освоите

Classification AlgorithmsReinforcement LearningSupervised LearningModel TrainingMachine Learning AlgorithmsUnsupervised LearningModel EvaluationArtificial Intelligence and Machine Learning (AI/ML)Data MiningArtificial IntelligenceLogistic RegressionPredictive ModelingDimensionality ReductionApplied Machine LearningStatistical AnalysisData PreprocessingData ManipulationModel Optimization

Программа курса

14 модулей · 109 учебных материалов

01Machine Learning: Introduction6 материалов

Machine Learning: Introduction

Introduction to the Course 'Intermediate Data Manipulation and Machine Learning'ЧтениеFull Specialization ResourcesЧтениеAI 101ВидеоMachine Learning 101Видео

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Packt - Course Instructors

Преподаватель курса

Intermediate Data Manipulation and Machine Learning
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Обучение на Coursera

≈ 16.8 ч

14 модулей

Язык: Английский

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

Часть программы вашего университета
ModelsВидео
Understanding Machine Learning BasicsDIALOGUE
02Machine Learning: Regression13 материалов

Machine Learning: Regression

Regression Types 101ВидеоUnivariate Regression 101ВидеоUnivariate Regression InteractiveВидеоUnivariate Regression LabВидеоUnivariate Regression ExerciseВидеоUnivariate Regression SolutionВидеоPolynomial Regression 101ВидеоPolynomial Regression LabВидеоMultivariate Regression 101ВидеоMultivariate Regression LabВидеоMultivariate Regression ExerciseВидеоMultivariate Regression SolutionВидеоUnderstanding Regression TypesDIALOGUE
03Machine Learning: Model Preparation and Evaluation8 материалов

Machine Learning: Model Preparation and Evaluation

Underfitting / Overfitting 101ВидеоTrain / Validation / Test Split 101ВидеоTrain / Validation / Test Split InteractiveВидеоTrain / Validation / Test Split LabВидеоResampling Techniques 101ВидеоResampling Techniques LabВидеоUnderstanding Underfitting and OverfittingDIALOGUEAssessment 1Задание
04Machine Learning: Regularization3 материалов

Machine Learning: Regularization

Regularization 101ВидеоRegularization LabВидеоUnderstanding Regularization Techniques in RegressionDIALOGUE
05Machine Learning: Classification Basics8 материалов

Machine Learning: Classification Basics

Confusion Matrix 101ВидеоROC Curve 101ВидеоROC Curve InteractiveВидеоROC Curve Lab IntroductionВидеоROC Curve Lab 1/3 (Data Prep, Modeling)ВидеоROC Curve Lab 2/3 (Confusion Matrix and ROC)ВидеоROC Curve Lab 3/3 (ROC, AUC, Cost Function)ВидеоEvaluating Binary Classification PerformanceDIALOGUE
06Machine Learning: Classification with Decision Trees6 материалов

Machine Learning: Classification with Decision Trees

Decision Trees 101ВидеоDecision Trees Lab (Introduction)ВидеоDecision Trees Lab (Coding)ВидеоDecision Trees ExerciseВидеоUsing Decision Trees for ClassificationDIALOGUEAssessment 2Задание
07Machine Learning: Classification with Random Forests6 материалов

Machine Learning: Classification with Random Forests

Random Forests 101ВидеоRandom Forests InteractiveВидеоRandom Forest Lab (Introduction)ВидеоRandom Forest Lab (Coding 1/2)ВидеоRandom Forest Lab (Coding 2/2)ВидеоExploring Random ForestsDIALOGUE
08Machine Learning: Classification with Logistic Regression6 материалов

Machine Learning: Classification with Logistic Regression

Logistic Regression 101ВидеоLogistic Regression Lab (Introduction)ВидеоLogistic Regression Lab (Coding 1/2)ВидеоLogistic Regression Lab (Coding 2/2)ВидеоLogistic Regression ExerciseВидеоIntroduction to Logistic RegressionDIALOGUE
09Machine Learning: Classification with Support Vector Machines7 материалов

Machine Learning: Classification with Support Vector Machines

Support Vector Machines 101ВидеоSupport Vector Machines Lab (Introduction)ВидеоSupport Vector Machines Lab (Coding 1/2)ВидеоSupport Vector Machines Lab (Coding 2/2)ВидеоSupport Vector Machines ExerciseВидеоExploring Support Vector Machines (SVM)DIALOGUEAssessment 3Задание
10Machine Learning: Classification with Ensemble Models2 материалов

Machine Learning: Classification with Ensemble Models

Ensemble Models 101ВидеоMastering Ensemble Learning TechniquesDIALOGUE
11Machine Learning: Association Rules8 материалов

Machine Learning: Association Rules

Association Rules 101ВидеоApriori 101ВидеоApriori Lab (Introduction)ВидеоApriori Lab (Coding 1/2)ВидеоApriori Lab (Coding 2/2)ВидеоApriori ExerciseВидеоApriori SolutionВидеоApplying Association Rules in Retail AnalysisDIALOGUE
12Machine Learning: Clustering12 материалов

Machine Learning: Clustering

Clustering OverviewВидеоkmeans 101Видеоkmeans LabВидеоkmeans ExerciseВидеоkmeans SolutionВидеоHierarchical Clustering 101ВидеоHierarchical Clustering InteractiveВидеоHierarchical Clustering LabВидеоDBSCAN 101ВидеоDBSCAN LabВидеоUnderstanding Clustering with DBSCANDIALOGUEAssessment 4Задание
13Machine Learning: Dimensionality Reduction13 материалов

Machine Learning: Dimensionality Reduction

PCA 101ВидеоPCA LabВидеоPCA ExerciseВидеоPCA SolutionВидеоt-SNE 101Видеоt-SNE Lab (Sphere)Видеоt-SNE Lab (MNIST)ВидеоFactor Analysis 101ВидеоFactor Analysis Lab (Introduction)ВидеоFactor Analysis Lab (Coding 1/2)ВидеоFactor Analysis Lab (Coding 2/2)ВидеоFactor Analysis ExerciseВидеоUnderstanding PCA through Dimensionality ReductionDIALOGUE
14Machine Learning: Reinforcement Learning11 материалов

Machine Learning: Reinforcement Learning

Reinforcement Learning 101ВидеоUpper Confidence Bound 101ВидеоUpper Confidence Bound InteractiveВидеоUpper Confidence Bound Lab (Introduction)ВидеоUpper Confidence Bound Lab (Coding 1/2)ВидеоUpper Confidence Bound Lab (Coding 2/2)ВидеоConclusion to the Course 'Intermediate Data Manipulation and Machine Learning'ЧтениеExploring Reinforcement Learning with PacmanDIALOGUEAssessment 5ЗаданиеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание