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.
Get an overview of the course. Perform image classification using pretrained networks. Use transfer learning to train customized classification networks.
Understand how information is passed between network layers and how different types of layers work.
Train networks from scratch. Understand how training algorithms work. Set training options to monitor and control training.
Choose and implement modifications to training algorithm options and training data to improve network performance.
Bring together image classification concepts that you have learned with a project.
Create convolutional networks that can predict continuous numeric responses.
Train networks to locate and label specific objects within images.
Build and train networks to perform classification on ordered sequences of data, such as time series or sensor data.
Use recurrent networks to create sequences of predictions.
Bring together signal classification concepts that you have learned with a project.
Learn next steps and give feedback on the course.
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Explore datos y cree modelos de predicción.
Aprenda flujos de trabajo prácticos de procesamiento de imágenes en MATLAB.
Domine los conceptos básicos para crear controladores inteligentes que aprenden de la experiencia.
Introducción rápida a los métodos de deep learning para reconocimiento de imágenes.