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Train Machine Learning Models · LearnSpace
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Train Machine Learning Models

Курс от CertNexus
Средний≈ 28.7 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course is designed for business professionals that wish to identify basic concepts that make up machine learning, test model hypothesis using a design of experiments and train, tune and evaluate models using algorithms that solve classification, regression and forecasting, and clustering problems. To be successful in this course a learner should have a background in computing technology, including some aptitude in computer programming.

Навыки, которые вы освоите

Model EvaluationMachine Learning AlgorithmsModel OptimizationClassification AlgorithmsUnsupervised LearningModel TrainingRegression AnalysisMachine LearningPerformance MetricApplied Machine LearningPredictive ModelingJupyterData PreprocessingMachine Learning Methods

Программа курса

5 модулей · 109 учебных материалов

01Prepare to Train a Machine Learning Model25 материалов

Overview

Course Intro: Train Machine Learning ModelsВидеоOverviewЧтениеGet help and meet other learners. Join your Community!Чтение

Machine Learning Concepts

Machine LearningВидео

Учитесь у экспертов

Stacey McBrine

CDSP, CAIP, CIoTP, CIoTSP, CFR, CISSP, SSCP, CASP, CFR, CEI, CEH, ECSA, CHFI, CCNA, CCSI, CTT+, LINUX+, PENTEST+, SECURITY+, A+, SCNP, ITIL Foundations, ITIL SO, ITIL OSA, MCSA, MCITP

Sarah Haq

Data Engineer at Artsy

Train Machine Learning 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

≈ 28.7 ч

5 модулей

Язык: Английский

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

Часть программы вашего университета
Machine Learning AlgorithmsВидео
Algorithm SelectionВидео
Iterative TuningВидео
Bias and VarianceВидео
Model GeneralizationВидео
The Bias–Variance TradeoffВидео
Holdout MethodВидео
Cross-ValidationЧтение
ParametersВидео
Guidelines for Training Machine Learning ModelsЧтение
Identifying Machine Learning ConceptsВзаимная проверка

Test a Hypothesis

Hypothesis and DOEВидеоHypothesis TestingВидеоA/B TestsВидеоAdditional Hypothesis Testing MethodsЧтениеp-valueВидеоConfidence IntervalВидео Guidelines for Testing a HypothesisЧтениеTesting a HypothesisВзаимная проверка

Evaluate What You've Learned

Preparing to Train a Machine Learning ModelЗаданиеReflect on What You've LearnedОбсуждение
02Develop Classification Models36 материалов

Overview

OverviewЧтение

Train Logistic Regression Models

Logistic RegressionВидеоMultinomial Logistic RegressionВидео Guidelines for Training Logistic Regression ModelsЧтениеTraining a Logistic Regression ModelЛабораторная

Train k-Nearest Neighbor Models

k-Nearest Neighbor (k-NN)Видео Guidelines for Training k-NN ModelsЧтениеTraining a k-NN ModelЛабораторная

Train Support-Vector Machine Models for Classification

Support-Vector Machines (SVMs)Видео Guidelines for Training SVM Classification ModelsЧтениеTraining an SVM Classification ModelЛабораторная

Train Naïve Bayes Models

Naïve BayesВидео Guidelines for Training Naïve Bayes ModelsЧтениеTraining a Naïve Bayes ModelЛабораторная

Train Tree-Based Models for Classification

Decision TreeВидеоCustomer Retention Example TreeВидеоCART HyperparametersЧтениеPruningВидеоEnsemble Learning and Random ForestsВидеоGradient BoostingВидео Guidelines for Training Classification Decision Trees and Ensemble Models

Tune Classification Models

Hyperparameter OptimizationВидео Guidelines for Tuning Classification ModelsЧтениеTuning Classification ModelsЛабораторная

Evaluate Classification Models

Evaluation MetricsВидеоClassification Model PerformanceВидеоConfusion MatrixВидеоAccuracy, Precision, Recall, and SpecificityВидеоPrecision–Recall Tradeoff and F₁ ScoreВидеоReceiver Operating Characteristic (ROC) CurveВидео

Evaluate What You've Learned

Developing Classification ModelsЗаданиеReflect on What You've LearnedОбсуждение
03Develop Regression Models26 материалов

Overview

OverviewЧтение

Train Linear Regression Models

Linear RegressionВидеоLinear Regression in Machine LearningВидеоMatrices in Linear RegressionВидеоNormal EquationВидео Guidelines for Training Linear Regression ModelsЧтениеTraining a Linear Regression ModelЛабораторная

Train Tree-Based Models for Regression

Regression Using Decision Trees and Ensemble ModelsВидео Guidelines for Training Regression Trees and Ensemble ModelsЧтениеTraining Regression Trees and Ensemble ModelsЛабораторная

Train Forecasting Models

ForecastingВидеоAutoregressive Integrated Moving Average (ARIMA)Видео Guidelines for Training Forecasting ModelsЧтение

Tune Regression Models

Cost FunctionВидеоRegularizationВидеоRegularization TechniquesЧтениеGradient DescentВидеоGrid/Randomized Search for RegressionВидео Guidelines for Tuning Regression ModelsЧтениеTuning Regression Models

Evaluate Regression Models

Mean Squared Error (MSE) and Mean Absolute Error (MAE)ВидеоCoefficient of DeterminationВидео Guidelines for Evaluating Regression ModelsЧтениеEvaluating Regression ModelsЛабораторная

Evaluate What You've Learned

Developing Regression ModelsЗаданиеReflect on What You've LearnedОбсуждение
04Develop Clustering Models20 материалов

Overview

OverviewЧтение

Train k-Means Clustering Models

k-Means ClusteringВидео Guidelines for Training k-Means Clustering ModelsЧтениеTraining a k-Means Clustering ModelЛабораторная

Train Hierarchical Clustering Models

Hierarchical ClusteringВидео Guidelines for Training Hierarchical Clustering ModelsЧтениеTraining a Hierarchical Clustering ModelЛабораторная

Tune Clustering Models

Latent Class AnalysisВидеоClustering Hyperparameters and TuningВидео Guidelines for Tuning Clustering ModelsЧтениеTuning Clustering ModelsЛабораторная

Evaluate Clustering Models

Evaluation Metrics for ClusteringВидеоElbow PointВидеоCluster Sum of SquaresВидеоSilhouette AnalysisВидеоWhen to Stop Hierarchical ClusteringВидео Guidelines for Evaluating Clustering ModelsЧтение

Evaluate What You've Learned

Developing Clustering ModelsЗаданиеReflect on What You've LearnedОбсуждение
05Apply What You've Learned2 материалов

Project

Course 4 ProjectЛабораторнаяOnline Retailer: Developing Classification, Regression, or Clustering ModelsВзаимная проверка
Чтение
Training Classification Decision Trees and Ensemble ModelsЛабораторная
Learning CurveВидео
Guidelines for Evaluating Classification ModelsЧтение
Evaluating Classification ModelsЛабораторная
Лабораторная
Evaluating Clustering ModelsЛабораторная