Familiarization with MATLAB ® AI toolboxes
Introductioin
MATLAB offers a lot of tools designed for developing artificial intelligence applications. From deep learning and computer vision to reinforcement learning and text analytics. In addition, MATLAB provides a collection of pretrained networks that help start projects, particularly in image and signal processing.
MATLAB provides several AI capabilities, including:
- Building AI models using minimal code or using pre-trained models
- Utilizing specialized tools and low-code applications to create scalable AI workflows
- Integrating AI with system-level simulations to prevent production errors
- Deploying AI models on high-performance platforms like edge devices and the cloud
- Facilitating seamless AI model and design integration between MATLAB and Python
1. DEEP LEARNING TOOLBOX
Formerly known as the Neural Network Toolbox, the Deep Learning Toolbox provides algorithms, network layers, pretrained models, and apps to design, train, analyze and simulate deep neural networks. Key Features:
- Custom Architectures: Create, train, and fine-tune custom network architectures.
- Visualization & Analysis: Tools for network visualization, layer analysis, and debugging.
- Hardware Acceleration: Support for GPU acceleration and integration with hardware like CUDA-enabled devices.
- Interoperability: Import models from frameworks such as TensorFlow and ONNX.