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Convolutional Neural Networks · LearnSpace
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Convolutional Neural Networks

Курс от DeepLearning.AI
Средний≈ 35.7 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more. By the end, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI.

Навыки, которые вы освоите

Convolutional Neural NetworksComputer VisionTransfer LearningDeep LearningTensorflowGenerative AINetwork ArchitectureEmbeddingsArtificial Neural NetworksModel OptimizationImage AnalysisFine-tuningData PreprocessingApplied Machine Learning

Программа курса

4 модулей · 82 учебных материалов

01Foundations of Convolutional Neural Networks21 материалов

Convolutional Neural Networks

Computer VisionВидеоEdge Detection ExampleВидеоMore Edge DetectionВидеоPaddingВидео

Учитесь у экспертов

Andrew Ng

Instructor

Kian Katanforoosh

Senior Curriculum Developer

Younes Bensouda Mourri

Curriculum developer

Convolutional Neural Networks
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 35.7 ч

4 модулей

Язык: Английский

Субтитры: Арабский, Французский, Бенгальский, Узбекский, 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
Join the DeepLearning.AI Forum to ask questions, get support, or share amazing ideas!Чтение
Strided ConvolutionsВидео
Convolutions Over VolumeВидео
One Layer of a Convolutional NetworkВидео
Clarifications about Upcoming Simple Convolutional Network Example VideoЧтение
Simple Convolutional Network ExampleВидео
Pooling LayersВидео
Clarifications about Upcoming CNN Example VideoЧтение
CNN ExampleВидео
Clarifications about Upcoming Why Convolutions?Чтение
Why Convolutions?Видео

Lecture Notes (Optional)

Lecture Notes W1Чтение

Quiz

The Basics of ConvNets Задание

Programming Assignments

(Optional) Downloading your Notebook, Downloading your Workspace and Refreshing your WorkspaceЧтениеConvolutional Model, Step by StepПрограммированиеConvolution Model ApplicationПрограммирование

Heroes of Deep Learning (Optional)

Yann LeCun InterviewВидео
02Deep Convolutional Models: Case Studies20 материалов

Case Studies

Why look at case studies?ВидеоClassic NetworksВидеоResNetsВидеоWhy ResNets Work?ВидеоNetworks in Networks and 1x1 ConvolutionsВидеоClarifications about Upcoming Inception Network Motivation VideoЧтениеInception Network MotivationВидеоInception NetworkВидеоMobileNetВидеоMobileNet ArchitectureВидеоEfficientNetВидео

Practical Advice for Using ConvNets

Using Open-Source ImplementationВидеоTransfer LearningВидеоData AugmentationВидеоState of Computer VisionВидео

Lecture Notes (Optional)

Lecture Notes W2Чтение

Quiz

Deep Convolutional Models Задание

Programming Assignments

Note on the Upcoming Programming Assignment - Residual NetworksЧтениеResidual NetworksПрограммированиеTransfer Learning with MobileNetПрограммирование
03Object Detection21 материалов

Detection Algorithms

Object LocalizationВидеоLandmark DetectionВидеоObject DetectionВидеоClarifications about Upcoming Convolutional Implementation of Sliding Windows VideoЧтениеConvolutional Implementation of Sliding WindowsВидеоBounding Box PredictionsВидеоIntersection Over UnionВидеоNon-max SuppressionВидеоAnchor BoxesВидеоClarifications about Upcoming YOLO Algorithm VideoЧтениеYOLO AlgorithmВидеоRegion Proposals (Optional)ВидеоSemantic Segmentation with U-NetВидеоTranspose ConvolutionsВидеоU-Net Architecture IntuitionВидеоU-Net ArchitectureВидео

Lecture Notes (Optional)

Lecture Notes W3Чтение

Quiz

Detection Algorithms Задание

Programming Assignments

Car detection with YOLOПрограммированиеClear Output Before Submitting (For U-Net Assignment)ЧтениеImage Segmentation with U-NetПрограммирование
04Special Applications: Face recognition & Neural Style Transfer20 материалов

Face Recognition

What is Face Recognition?ВидеоOne Shot LearningВидеоSiamese NetworkВидеоTriplet LossВидеоClarifications about Upcoming Face Verification and Binary Classification VideoЧтениеFace Verification and Binary ClassificationВидео

Neural Style Transfer

What is Neural Style Transfer?ВидеоWhat are deep ConvNets learning?ВидеоCost FunctionВидеоContent Cost FunctionВидеоClarifications about Upcoming Style Cost Function VideoЧтениеStyle Cost FunctionВидео

Lecture Notes (Optional)

Lecture Notes W4Чтение

Quiz

Special Applications: Face Recognition & Neural Style Transfer Задание

End of access to Lab Notebooks

[IMPORTANT] Reminder about end of access to Lab NotebooksЧтение

Programming Assignments

Face RecognitionПрограммированиеArt Generation with Neural Style TransferПрограммирование

References & Acknowledgments

ReferencesЧтениеAcknowledgmentsЧтение
1D and 3D GeneralizationsВидео