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Build Regression, Classification, and Clustering Models · LearnSpace
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Build Regression, Classification, and Clustering Models

Курс от CertNexus
Средний≈ 20.3 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

In most cases, the ultimate goal of a machine learning project is to produce a model. Models make decisions, predictions—anything that can help the business understand itself, its customers, and its environment better than a human could. Models are constructed using algorithms, and in the world of machine learning, there are many different algorithms to choose from. You need to know how to select the best algorithm for a given job, and how to use that algorithm to produce a working model that provides value to the business. This third course within the Certified Artificial Intelligence Practitioner (CAIP) professional certificate introduces you to some of the major machine learning algorithms that are used to solve the two most common supervised problems: regression and classification, and one of the most common unsupervised problems: clustering. You'll build multiple models to address each of these problems using the machine learning workflow you learned about in the previous course. Ultimately, this course begins a technical exploration of the various machine learning algorithms and how they can be used to build problem-solving models.

Навыки, которые вы освоите

Model EvaluationRegression AnalysisClassification AlgorithmsLinear AlgebraModel TrainingUnsupervised LearningModel OptimizationApplied Machine LearningMachine Learning MethodsSupervised LearningStatistical ModelingMachine Learning AlgorithmsPerformance TuningPredictive ModelingMachine Learning

Программа курса

6 модулей · 92 учебных материалов

01Build Linear Regression Models Using Linear Algebra19 материалов

Overview

Course Intro: Build Regression, Classification, and Clustering ModelsВидеоBuild Linear Regression Models Using Linear Algebra Module IntroductionВидеоOverviewЧтениеGet help and meet other learners. Join your Community!Чтение

Linear Algebra and Linear Regression

Учитесь у экспертов

Anastas Stoyanovsky

Watson Senior Software Engineer, Software Architect at IBM

Build Regression, Classification, and Clustering Models
В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 20.3 ч

6 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Нидерландский, Корейский, Немецкий, Пушту, Русский, Тайский, Индонезийский, Шведский, Турецкий, Испанский, Дари, Хинди, Японский, Казахский, Польский

Часть программы вашего университета
Linear RegressionВидео
Linear EquationВидео
Straight Line Fit to Data ExampleВидео
Linear Regression in Machine LearningВидео
Matrices in Linear RegressionВидео
Normal EquationВидео
Advanced Linear ModelsВидео

Evaluate Linear Regression Models

Cost FunctionВидеоMSE and MAEВидеоCoefficient of DeterminationВидеоNormal Equation ShortcomingsВидеоGuidelines for Building a Regression Model Using Linear AlgebraЧтениеBuilding a Regression Model Using Linear AlgebraЛабораторная

Evaluate What You've Learned

Building Linear Regression Models Using Linear AlgebraЗаданиеReflect on What You've LearnedОбсуждение
02Build Regularized and Iterative Linear Regression Models15 материалов

Overview

Build Regularized and Iterative Linear Regression Models Module IntroductionВидеоOverviewЧтение

Build Regularized Regression Models

Regularization TechniquesВидеоRidge RegressionВидеоLasso RegressionВидеоElastic Net RegressionВидеоGuidelines for Building a Regularized Linear Regression ModelЧтениеBuilding a Regularized Linear Regression ModelЛабораторная

Build Iterative Regression Models

Iterative ModelsВидеоGradient DescentВидеоGradient Descent TechniquesВидеоGuidelines for Building an Iterative Linear Regression ModelЧтениеBuilding an Iterative Linear Regression ModelЛабораторная

Evaluate What You've Learned

Building Regularized and Iterative Linear Regression ModelsЗаданиеReflect on What You've LearnedОбсуждение
03Train Classification Models16 материалов

Overview

Train Classification Models Module IntroductionВидеоOverviewЧтение

Train Binary Classification Models

Linear Regression ShortcomingsВидеоLogistic RegressionВидеоDecision BoundaryВидеоCost Function for Logistic RegressionВидеоk-Nearest Neighbor (k-NN)ВидеоLogistic Regression vs. k-NNВидеоGuidelines for Training Binary Classification ModelsЧтениеTraining Binary Classification ModelsЛабораторная

Train Multi-Class Classification Models

Multi-Label and Multi-Class ClassificationВидеоMultinomial Logistic RegressionВидеоGuidelines for Training Multi-Class Classification ModelsЧтениеTraining a Multi-Class Classification ModelЛабораторная

Evaluate What You've Learned

Training Classification ModelsЗаданиеReflect on What You've LearnedОбсуждение
04Evaluate and Tune Classification Models23 материалов

Overview

Evaluate and Tune Classification Models Module IntroductionВидеоOverviewЧтение

Evaluate Classification Models

Model PerformanceВидеоConfusion MatrixВидеоClassifier Performance MeasurementВидеоAccuracyВидеоPrecisionВидеоRecallВидеоF₁ ScoreВидеоReceiver Operating Characteristic (ROC) CurveВидеоThresholds and AUCВидеоPrecision–Recall Curve (PRC)ВидеоGuidelines for Evaluating Classification ModelsЧтениеEvaluating a Classification ModelЛабораторная

Tune Classification Models

Hyperparameter OptimizationВидеоGrid SearchВидеоRandomized SearchВидеоBayesian OptimizationВидеоGenetic AlgorithmsВидеоGuidelines for Tuning Classification ModelsЧтениеTuning a Classification Model

Evaluate What You've Learned

Evaluating and Tuning Classification ModelsЗаданиеReflect on What You've LearnedОбсуждение
05Build Clustering Models17 материалов

Overview

Build Clustering Models Module IntroductionВидеоOverviewЧтение

Build k-Means Clustering Models

k-Means ClusteringВидеоGlobal vs. Local OptimizationВидеоElbow PointВидеоCluster Sum of SquaresВидеоSilhouette AnalysisВидеоAdditional Cluster Analysis MethodsЧтениеGuidelines for Building a k-Means Clustering ModelЧтениеBuilding a k-Means Clustering ModelЛабораторная

Build Hierarchical Clustering Models

k-Means Clustering ShortcomingsВидеоHierarchical ClusteringВидеоDendrogramВидеоGuidelines for Building a Hierarchical Clustering ModelЧтениеBuilding a Hierarchical Clustering ModelЛабораторная

Evaluate What You've Learned

Building Clustering ModelsЗаданиеReflect on What You've LearnedОбсуждение
06Apply What You've Learned2 материалов

Project

Course 3 ProjectЛабораторнаяBuilding a Regression, Classification, or Clustering ModelВзаимная проверка
Лабораторная