This week we tilt our spotlight to a product created by renowned software company, MathWorks. MATLAB for Artificial Intelligence is used to design AI models and AI-driven systems.
MATLAB can be used for a range of applications, including deep learning and machine learning, signal processing and communications, image and video processing, control systems, test and measurement, computational finance, and computational biology. This article is focused on MATLAB for Deep Learning.
What is Deep Learning?
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. In deep learning, a computer model learns directly from pictures, text, or sound to perform classification tasks.
How does MATLAB assist in Deep Learning?
With tools and functions for managing large data sets, MATLAB provides specialized toolboxes for working with machine learning, neural networks, computer vision, and automated driving. With a few lines of code, MATLAB lets one work on deep learning without any expert help.
Prepare and Label Image, Time-Series, and Text Data: MATLAB significantly reduces the time required to preprocess and label datasets with domain-specific apps for audio, video, images, and text data
Simulate and Generate Synthetic Data: Data for accurate models can become really critical. MATLAB is capable of generating more data when there is a paucity of the right scenarios
Deploy Trained Networks: This tool is capable of deploying your trained model on embedded systems, enterprise systems, FPGA devices, or the cloud
Deep learning models can achieve state-of-the-art accuracy, sometimes exceeding human-level performance. Models are trained by using a large set of labeled data and neural network architectures that contain many layers
Use Case
Shell’s transformation using MATLAB’s Distributed Computing Server and Machine Vision Tools
Automated LiDAR Point-Cloud Annotation for Sensor Verification
Capability
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Train deep learning networks for classification, regression, and feature learning on image, time-series, numeric, and text data
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Build, visualize, experiment with, and analyze deep learning networks using interactive apps
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Import pre-trained models into MATLAB for inference
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Visualize training progress & activations of the learned features in a deep learning network
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Speed up deep learning training using GPU, cloud, & distributed computing
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Simulate & deploy trained networks to embedded systems or integrate them into production environments
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Using neural networks with a variety of supervised & unsupervised shallow neural network architectures
Conclusion
MATLAB is a powerful tool that gives organizations, researchers, and experts the flexibility to build deep learning models without having to learn another language. Whether one needs to analyze data, develop algorithms, or create models, MATLAB is designed to assist in all possible ways.
From deploying enterprise applications to running on embedded devices, MATLAB’s solutions cater to a variety of use-cases. All in all, MathWorks does stand true to its words on being one of the leading developers of mathematical computing software for engineers and scientists.
What is the Product spotlight?
Product spotlight is our effort to bring unique and innovative AI products that can help businesses and their customers deliver quality and exceptional service. It is a bi-weekly blog that focuses on a single product and how that can help create value.
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