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Deep Learning con MATLAB

Implemente flujos de trabajo comunes de deep learning en MATLAB® utilizando datos de imágenes y secuencias de la vida real. Profundice en algunas ideas detrás de los algoritmos de deep learning y las arquitecturas estándar de redes.

Módulos del curso

Classifying Images with Convolutional Networks

Get an overview of the course. Perform image classification using pretrained networks. Use transfer learning to train customized classification networks.

Lecciones:
  • Course Overview
  • Deep Learning Basics

Understanding Convolutional Neural Networks

Understand how information is passed between network layers and how different types of layers work.

Lecciones:
  • Understanding Neural Networks
  • Convolutional Layers
  • Viewing Filters
  • Viewing the Activations of Different Layers
  • Review - Understanding Convolutional Neural Networks

Creating and Training Networks

Train networks from scratch. Understand how training algorithms work. Set training options to monitor and control training.

Lecciones:
  • Training from Scratch
  • Creating Network Architectures
  • Understanding Network Training
  • Monitoring Training Progress
  • Validation
  • Review - Creating and Training Networks

Improving Performance

Choose and implement modifications to training algorithm options and training data to improve network performance.

Lecciones:
  • Troubleshooting Methods
  • Visualizing Network Predictions
  • Augmented Datastores
  • Training Options
  • Experiment Manager
  • Review - Improving Performance

Image Classification Project

Bring together image classification concepts that you have learned with a project.

Lecciones:
  • Project - Classify Fashion Images

Performing Regression

Create convolutional networks that can predict continuous numeric responses.

Lecciones:
  • What is Regression
  • Transfer Learning for Regression
  • Evaluating a Regression Network
  • Review - Performing Regression

Using Deep Learning for Computer Vision

Train networks to locate and label specific objects within images.

Lecciones:
  • Computer Vision Applications
  • Ground Truth
  • YOLO Object Detectors
  • Evaluating Object Detectors
  • Review - Deep Learning for Computer Vision

Classifying Sequence Data with Recurrent Networks

Build and train networks to perform classification on ordered sequences of data, such as time series or sensor data.

Lecciones:
  • Course Example - Classify Flooding Level
  • Managing Collections of Signal Data
  • Long Short-Term Memory Networks
  • Sequence Classification
  • Improving LSTM Performance
  • Review - Classifying Sequence Data with Recurrent Networks

Classifying Sequences of Output

Use recurrent networks to create sequences of predictions.

Lecciones:
  • Course Example - Classify Regions of Flooding Levels
  • Labeling Regions of Interest
  • Sequence-to-Sequence Classification
  • Review - Classifying Sequences of Output

Sequence Classification Project

Bring together signal classification concepts that you have learned with a project.

Lecciones:
  • Project - Robot Navigation

Conclusion

Learn next steps and give feedback on the course.

Lecciones:
  • Summary
  • Additional Resources
  • Survey

Formato:A su ritmo

Idioma:Español

Idioma

  • Ejercicios prácticos con comentarios automáticos
  • Acceda a MATLAB a través de su navegador web
  • Informe de progreso y certificado del curso disponibles para compartir

Machine Learning con MATLAB

Explore datos y cree modelos de predicción.

Procesamiento de imágenes con MATLAB

Aprenda flujos de trabajo prácticos de procesamiento de imágenes en MATLAB.

Reinforcement Learning Onramp

Domine los conceptos básicos para crear controladores inteligentes que aprenden de la experiencia.

Deep Learning Onramp

Introducción rápida a los métodos de deep learning para reconocimiento de imágenes.