К содержимому
learnspaceYOUR NEXT CHAPTER
ПРОСТРАНСТВО ОБУЧЕНИЯ
ГлавнаяКаталог курсовМоё обучениеCoursera

Знания без границ

Учитесь у лучших университетов и компаний мира.

Открыть Coursera
Интеграция
Пространство университета
Моё пространствоСтраница курса
↵
ЯЛичный кабинетСтудент
© 2026 LearnSpaceКаждый день — возможность узнать больше.Помощь
Introduction to Machine Learning · LearnSpace
Назад в каталог
courseraАнализ данных

Introduction to Machine Learning

Курс от Duke University
Средний≈ 25.8 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course provides a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) and demonstrates how they can solve complex problems in various industries, from medical diagnostics to image recognition to text prediction. Through hands-on practice exercises, you'll implement these data science models on datasets, gaining proficiency in machine learning algorithms with PyTorch, used by leading tech companies like Google and NVIDIA.

Навыки, которые вы освоите

Logistic RegressionModel OptimizationModel TrainingDeep LearningTransfer LearningConvolutional Neural NetworksNatural Language ProcessingSupervised LearningPython ProgrammingApplied Machine LearningReinforcement LearningImage AnalysisComputer VisionUnsupervised LearningMachine LearningMedical ImagingMachine Learning MethodsArtificial Neural NetworksPyTorch (Machine Learning Library)

Программа курса

6 модулей · 111 учебных материалов

01Simple Introduction to Machine Learning39 материалов

Logistic Regression

Course Information ЧтениеWhy Machine Learning Is ExcitingВидеоWhat Is Machine Learning?ВидеоIntro to Machine LearningЗадание

Учитесь у экспертов

Lawrence Carin

Provost of King Abdullah University

David Carlson

Assistant Professor of Civil and Environmental Engineering

Timothy Dunn

Postdoctoral Associate

Kevin Liang

PhD Candidate

Introduction to Machine Learning
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

≈ 25.8 ч

6 модулей

Язык: Английский

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

Часть программы вашего университета
Logistic RegressionВидео
Interpretation of Logistic RegressionВидео
Math for Data ScienceЧтение
Motivation for Multilayer PerceptronВидео
Logistic RegressionЗадание
Python PrerequisitesЛабораторная
Report a problem with the course Чтение

Multilayer Perceptron

Multilayer Perceptron ConceptsВидеоMultilayer Perceptron Math ModelВидеоMultilayer PerceptronЗаданиеDeep LearningВидеоExample: Document AnalysisВидеоInterpretation of Multilayer PerceptronВидеоTransfer LearningВидеоDeep LearningЗаданиеModel SelectionВидеоModel SelectionЗаданиеEarly History of Neural NetworksВидеоHistory of Neural NetworksЗадание

Convolutional Neural Networks

Hierarchical Structure of ImagesВидеоConvolution FiltersВидеоConvolutional Neural NetworkВидеоCNN ConceptsЗаданиеCNN Math ModelВидеоHow the Model LearnsВидеоAdvantages of Hierarchical FeaturesВидеоCNN Math ModelЗадание

Applications in the Real World

CNN on Real ImagesВидеоApplications in Use and PracticeВидеоDeep Learning and Transfer LearningВидеоApplications In Use and PracticeЗаданиеWeek 1 ComprehensiveЗаданиеPyTorch InstallationЛабораторнаяCoding EnvironmentsЛабораторная

PyTorch Basics

Introduction to PyTorchВидео
02Basics of Model Learning11 материалов

Logistic Regression as Running Example

How Do We Define Learning?ВидеоHow Do We Evaluate Our Networks?ВидеоLesson OneЗадание

Learning via Gradient Descent

How Do We Learn Our Network?ВидеоHow Do We Handle Big Data?ВидеоEarly StoppingВидеоLesson 2Задание

Model Learning with PyTorch

Week 2 ComprehensiveЗаданиеModel Learning with PyTorchВидеоLogistic RegressionЛабораторнаяMulti-Layer Perceptron (MLP) AssignmentЛабораторная
03Image Analysis with Convolutional Neural Networks14 материалов

Convolutional Neural Network Basics

Motivation: Diabetic RetinopathyВидеоBreakdown of the Convolution (1D and 2D)ВидеоLesson OneЗадание

Core Components of the Network

Core Components of the Convolutional LayerВидеоActivation FunctionsВидеоPooling and Fully Connected LayersВидеоLesson 2Задание

CNN Implementation

Training the NetworkВидеоTransfer Learning and Fine-TuningВидеоLesson 3Задание

Convolutional Neural Networks with PyTorch

Week 3 ComprehensiveЗаданиеCNN with PyTorchВидеоConvolutional Neural NetworksЛабораторнаяCNN AssignmentЛабораторная
04Recurrent Neural Networks for Natural Language Processing19 материалов

Word embeddings

Introduction to the Concept of Word VectorsВидеоWords to VectorsВидеоExample of Word EmbeddingsВидеоLesson 1Задание

Representative example NLP problem: Sentiment Analysis

Neural Model of TextВидеоThe Softmax FunctionВидеоMethods for Learning Model ParametersВидеоMore Details on How to Learn Model ParametersВидеоLesson 2Задание

Recurrent Neural Networks and Long Short-Term Memory

The Recurrent Neural NetworkВидеоLong Short-Term MemoryВидеоLong Short-Term Memory ReviewВидеоUse of LSTM for Text SynthesisВидеоLesson 3Задание

Alternative Approaches

Simple and Effective Alternative Methods for Neural NLPВидеоWeek 4 ComprehensiveЗадание

Natural Language Processing with PyTorch

Natural Language Processing with PyTorchВидеоNatural Language ProcessingЛабораторнаяNatural Language Processing AssignmentЛабораторная
05The Transformer Network for Natural Language Processing12 материалов

Inner Products

Word Vectors and Their InterpretationВидеоRelationships Between Word VectorsВидеоInner Products Between Word VectorsВидеоIntuition Into Meaning of Inner Products of Word VectorsВидео

Attention Mechanism

Introduction of Attention Mechanism ВидеоQueries, Keys, and Values of Attention NetworkВидеоSelf-Attention and Positional EncodingsВидео

Sequence-to-Sequence Encoder and Decoder

Attention-Based Sequence EncoderВидеоCoupling the Sequence Encoder and Decoder ВидеоCross Attention in the Sequence-to-Sequence ModelВидео

The Transformer Network

Multi-Head AttentionВидеоThe Complete Transformer NetworkВидео
06Introduction to Reinforcement Learning16 материалов

Reinforcement Learning

Introduction to Reinforcement LearningВидеоReinforcement Learning Problem SetupВидеоExample of Reinforcement Learning in PracticeВидеоReinforcement Learning QuizЗаданиеReinforcement Learning with PyTorchВидеоReinforcement LearningЛабораторнаяReinforcement Learning AssignmentЛабораторная

Q Learning

Moving to a Non-Myopic PolicyВидеоQ LearningВидеоExtensions of Q LearningВидеоQ Learning QuizЗадание

Deep Q Learning

Limitations of Q Learning, and Introduction to Deep Q LearningВидеоDeep Q Learning Based on ImagesВидеоConnecting Deep Q Learning with Conventional Q LearningВидеоDeep Q Learning QuizЗаданиеShare your learning experienceЧтение