Artificial Intelligence

Apply machine learning and deep learning

Posts 1 - 10 of 12

다음에 대한 결과: New features

Introducing the Reduced Order Modeler App: How to Interactively Create AI-Based Reduced Order Models (ROMs)

The following blog post is from Melda Ulusoy, Principal Product Marketing Manager at MathWorks, and Kishen Mahadevan, Senior Product Manager at MathWorks. Reduced order modeling is a collection of... 더 읽어보기 >>

Apply AI with New R2024b Examples

In my last post, I talked about new AI features introduced with MATLAB R2024b - the latest release, which is now available to you. In this blog post, I am going to present a few new and exciting... 더 읽어보기 >>

R2024b: A Peek into New AI Features

MATLAB R2024b is the latest release and available for you to try. I am here to talk specifically about new AI features in the latest release, and if you're interested in other features, check out... 더 읽어보기 >>

Simulate PyTorch and Other Python-Based Models with Simulink Co-Execution Blocks

This blog post is from Maggie Oltarzewski, Product Marketing Engineer at MathWorks. In R2024a, four new blocks for co-executing deep learning models in Simulink were added to Deep Learning... 더 읽어보기 >>

Export Models from Machine Learning Apps to Simulink

In this blog post, I am going to show you the most interactive way to create a Simulink model that includes a machine learning model by using the Classification Learner app. Simulating and testing... 더 읽어보기 >>

Explainability in Object Detection for MATLAB, TensorFlow, and PyTorch Models

In R2024a, Deep Learning Toolbox Verification Library introduced the d-rise function. D-RISE is an explainability tool that helps you visualize and understand  which parts are important for object... 더 읽어보기 >>

Building Confidence in AI with Constrained Deep Learning

Constrained deep learning is an advanced approach to training robust deep neural networks by incorporating constraints into the learning process. These constraints can be based on physical laws,... 더 읽어보기 >>

Data Type Conversion Between MATLAB and Python: What’s New in R2024a 2

When combining MATLAB with Python® to create deep learning workflows, data type conversion between the two frameworks can be time consuming and sometimes perplexing. I 've certainly experimented... 더 읽어보기 >>

Convert Deep Learning Models between PyTorch, TensorFlow, and MATLAB 3

In this blog post we are going to show you how to use the newest MATLAB functions to: Import models from TensorFlow and PyTorch into MATLAB Export models from MATLAB to TensorFlow and... 더 읽어보기 >>

Tips on Accelerating Deep Learning Training

Deep learning models are trained by using large sets of labeled data. Training a deep learning model can be time-consuming; it can take from hours to days. In this blog post, we will provide a few... 더 읽어보기 >>

Posts 1 - 10 of 12