学习理论和实践知识,使用真实的图像和序列数据构建深度神经网络。
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.
格式:自定进度
语言:中文
了解 MATLAB 的核心功能以进行数据分析、建模和编程。
使用深度学习方法执行图像识别快速入门。
探查数据并构建预测模型。
MATLAB 基础知识快速入门。
了解 MATLAB 的核心功能以进行数据分析、建模和编程。
使用深度学习方法执行图像识别快速入门。