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Foundations of Machine Learning · LearnSpace
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Foundations of Machine Learning

Курс от Fractal Analytics
Начальный≈ 25.6 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

In a world where data-driven insights are reshaping industries, mastering the foundations of machine learning is a valuable skill that opens doors to innovation and informed decision-making. In this comprehensive course, you will be guided through the core concepts and practical aspects of machine learning. Complex algorithms and techniques will be demystified and broken down into digestible knowledge, empowering you to wield the capabilities of machine learning confidently. By the end of this course, you will: 1. Grasp the fundamental principles of machine learning and its real-world applications. 2. Construct and evaluate machine learning models, transforming raw data into actionable insights. 3. Navigate through diverse datasets, extracting meaningful patterns that drive decision-making. 4. Apply machine learning strategies to varied scenarios, expanding your problem-solving toolkit. This course equips you with the foundation to thrive as a machine learning enthusiast, data-driven professional, or someone ready to explore the dynamic possibilities of machine learning.

Навыки, которые вы освоите

Model EvaluationData PreprocessingUnsupervised LearningPredictive ModelingRegression AnalysisFeature EngineeringDecision Tree LearningLogistic RegressionClassification AlgorithmsSupervised LearningModel OptimizationMachine LearningMachine Learning MethodsMachine Learning AlgorithmsModel DeploymentApplied Machine LearningAnomaly DetectionModel Training

Программа курса

6 модулей · 95 учебных материалов

01Introduction to Machine Learning15 материалов

Course Introduction

Gateway to the CourseВидеоCourse and Instructor Introduction VideoВидеоSyllabus - Foundation of Machine LearningЧтение

Build your first Predictive model for Synergix Solutions

Introduction to Problem StatementВидео

Учитесь у экспертов

Analytics Vidhya

Преподаватель курса

Foundations of Machine Learning
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Обучение на Coursera

≈ 25.6 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, Венгерский, Польский

Часть программы вашего университета
Reading material - Understanding the DataЧтение
How do we Make Predictions?Видео
Methodology of Evaluating PredictionsВидео
Introduction to Data DivisionВидео
Building Benchmark Models and Evaluating ItВидео
Mastering Your Prediction Process & Reflecting on Data-Driven Decision MakingDIALOGUE
Introduction to Machine LearningВидео
Applications of Machine LearningВидео
Types of Machine LearningВидео
ML Strategy Consultation: Advising TechStart InnovationsDIALOGUE
Introduction to MLЗадание
02Building Your First Machine Learning (ML) Model for Synergix Solutions22 материалов

Data Preprocessing for Synergix Solutions

ML WorkflowВидеоTasks to be PerformedВидеоCombining Product Attribute Data with POS DataВидеоCombining all the tables in the DataframeВидеоUnderstanding the Combined DataВидеоTreating Missing Values - Part 1ВидеоTreating Missing Values Part 2ВидеоOutlier Detection and TreatmentВидеоPreparing the Dataset for Supervised and Unsupervised ModelsВидеоGenerative AI for Data AnalysisВидеоPreprocessing Data for Anova InsuranceПрограммирование

Introduction to KNN Algorithm

Introduction to KNNВидеоBuilding a kNN modelВидеоChoosing the Optimal KВидеоDifferent Ways to Calculate DistanceВидеоProblems with Distance Based AlgorithmВидео

Building the KNN Model

Sklearn to build Optimal Process to Build an ML ModelВидеоBuilding a Knn classification model and evaluating itВидеоChoosing the right K valueВидеоBias and VarianceВидеоBuilding your first ML modelЗаданиеNew QuizЗадание
03Evaluating Prediction Models13 материалов

Evaluation Metrics for Classification Models

Understanding Confusion Matrix and AccuracyВидеоA deep dive into Precision, Recall and F1 ScoreВидеоUnderstanding the AU-ROC curveВидео

Evaluation Metrics for Regression Models

Why do we calculate RMSEВидеоUnderstanding R2 Score and Adjusted R2 ScoreВидео

Data Division

Train-Test SplitВидеоTrain-Test split ratio and limitВидеоCross validationВидеоImplementing Cross validationВидеоBenchmark ModelsВидеоPractice QuizЗаданиеBuild and Evaluating KNN model for Anova InsuranceПрограммированиеHow to Evaluate a ModelЗадание
04Linear and Logistic Regression17 материалов

Linear Regression

Introduction to Linear RegressionВидеоSignificance of Slope and Intercept in the linear regressionВидеоHow Model Decides The Best-Fit LineВидеоLet’s Build a Simple Linear Regression ModelВидеоModel Understanding Using Descriptive ApproachВидеоModel Understanding Using Descriptive Approach - IIВидеоModel Building Using Predictive ApproachВидеоLinear regressionЗадание

Logistic Regression

IntroductionВидеоLines to Curves with Logistic RegressionВидеоReading Between the Curves with Log LossВидеоStats Model SummaryВидеоFeature Selection and ScalingВидеоPredictive model in Logistic RegressionВидео
05Decision Trees for Synergix Solution13 материалов

Introduction to Decision Trees

Introduction to Decision TreesВидеоLet’s Visualize The Decision TreeВидеоHow Do Decision Trees Decide?ВидеоHow Decision Trees Make Predictions?ВидеоHands on: Building the Decision Tree Classification ModelВидеоHyperparameters of Decision TreesВидеоHands on: Building the Decision Tree Classification Model - Part 2ВидеоBuilding a Decision Tree Regression ModelВидеоHandling Imbalanced DatasetsВидеоHandling Imbalanced Datasets - Hands onВидеоPractice QuizЗаданиеCheck your understanding for Decision TreesЗаданиеBuilding Decision Trees for Anova InsuranceПрограммирование
06Introduction to Unsupervised Learning15 материалов

K-means Clustering Algorithm

Setting the ContextВидеоChoosing Clustering AlgorithmsВидеоSolving our Problem using k-means - Part 1ВидеоSolving our Problem using k-means - Part 2ВидеоFinding optimal K valueВидеоAnalysis and Insights Based on the PlotВидео

Other Clustering Algorithms

Introduction to Hierarchical Clustering Analysis (HCA)ВидеоSolving our Problem using Hierarchical ClusteringВидеоIntroduction to DBSCANВидеоSolving our Problem using DBSCAN ClusteringВидеоApplications of Clustering in the Real WorldЧтениеPractice QuizЗадание
New QuizЗадание
Building a Logistic Model for Anova InsuranceПрограммирование
Logistic regressionЗадание
Course SummaryВидео
KMeans Model for TapToBuyПрограммирование
Unsupervised MLЗадание