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MATLAB在数据科学中的应用:
Explore data; build machine learning models;
do predictive analytics
MATLAB® makes data science easy with tools to access and preprocess data, build machine learning and predictive models, and deploy models to enterprise IT systems.
Access data stored in flat files, databases, data historians, and cloud storage, or connect to live sources such as data acquisition hardware and financial data feeds
Manage and clean data using datatypes and preprocessing capabilities for programmatic and interactive data preparation, including apps for ground-truth labeling
Document data analysis with MATLAB graphics and the Live Editor notebook environment
Apply domain-specific feature engineering techniques for sensor, text, image, video, and other types of data
Explore a wide variety of modeling approaches using machine learning and deep learning apps
Fine-tune machine learning and deep learning models with automated feature selection and hyperparameter tuning algorithms
Deploy machine learning models to production IT systems, without recoding into another language
Automatically convert machine learning models to standalone C/C++ code
面向嵌入式系统的 MATLAB 和 Simulink
设计、编码和验证嵌入式系统
只需按一下按钮,您就可以使用 MATLAB® 和 Simulink® 生成代码并在硬件上运行代码。但是,编码只是其中一项任务 - 了解从原型设计到生产的过程中如何使用 MATLAB 和 Simulink 设计、编码和验证您的下一个嵌入式系统。您可以:
生成优化的 C、C++、CUDA、Verilog、VHDL 及结构化文本
使用浮点和定点设计工具,在成本与性能之间做出权衡
使用在环测试,验证和分析生成的代码
符合各种标准的要求,例如 AUTOSAR、ISO 26262、DO-178、MISRA C 及 CERT C
使用硬件支持包附加组件,在 从 Arduino® 到 Zynq® 的流行电路板上进行原型设计
Measurement and instrumentation
Measurement and Instrumentation
Examples: iPhone and Android ThingSpeak, Analog Devices® ADALM1000, serial, TCP/IP, UDP, or Bluetooth®
Create Custom Graphics and Interactions
Extend the graphics system with customized defaults and share with your co-workers to adopt a common standard across your team.
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