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ai、数据科学和统计 -凯发k8网页登录

针对机器学习和深度神经网络进行数据准备、设计、仿真和部署

matlab® 让数据科学工作变得轻松,借助其中的工具,您可以访问和预处理数据、构建机器学习和预测模型,以及部署模型。

使用 app 或仅需几行 matlab 代码,您就可以将统计、机器学习和深度学习方法应用于您的工作中,以设计算法、准备和标注数据,或生成代码并将其部署到嵌入式系统中。使用专业工具扩展 ai 建模和数据拟合工作流,以用于:

  • 图像、视频、信号、音频和文本等数据类型

  • 计算机视觉、音频和信号处理、文本分析、无线通信和自动驾驶等应用。

workflow for ai from data preparation to modeling to system design and deployment

主题

ai 基础

  • machine learning in matlab (statistics and machine learning toolbox)
    discover machine learning capabilities in matlab for classification, regression, clustering, and deep learning, including apps for automated model training and code generation.
  • 在 matlab 中进行深度学习 (deep learning toolbox)
    通过使用卷积神经网络进行分类和回归来探索 matlab 的深度学习能力,包括预训练网络和迁移学习,以及在 gpu、cpu、集群和云上进行训练。
  • what is reinforcement learning? (reinforcement learning toolbox)
    reinforcement learning is a goal-directed computational approach where a computer learns to perform a task by interacting with an uncertain dynamic environment.

ai 建模

仿真和部署

  • (deep learning toolbox)
    this example shows how to use a feedforward deep learning network inside a simulink® model to predict the state of charge (soc) of a battery.
  • code generation for deep learning networks (gpu coder)
    get started with cuda code generation for image classification networks such as mobilenet-v2, resnet, and googlenet.
  • (embedded coder)
    this example shows how to generate c code from a simulink® model that performs lane and vehicle detection using convolutional neural networks (cnn).

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