Add essential MATLAB toolboxes to devcontainer configurations

[Copilot]

This PR adds six essential MATLAB toolboxes to the devcontainer configurations to provide a more comprehensive MATLAB environment for GitHub Codespaces users.

Added Toolboxes

The following toolboxes are now included in the MATLAB installations:

• Parallel Computing Toolbox - For parallel and distributed computing
• Deep Learning Toolbox - For neural networks and deep learning workflows
• Optimization Toolbox - For solving optimization problems
• Signal Processing Toolbox - For signal analysis and processing
• Image Processing Toolbox - For image analysis and computer vision
• Computer Vision Toolbox - For computer vision algorithms and applications

Changes Made

Updated three devcontainer configurations to include the new toolboxes:

1. .devcontainer/using-matlab-dockerfile/Dockerfile - Updated the default MATLAB_PRODUCT_LIST ARG
2. .devcontainer/using-matlab-dockerfile/devcontainer.json - Updated build arguments for Docker-based setup
3. .devcontainer/using-devcontainer-feature/devcontainer.json - Updated products list for feature-based setup

All existing toolboxes (Symbolic Math Toolbox, Simulink) are preserved to maintain backward compatibility.

Impact

Users selecting the "Customize MATLAB installation with specific toolboxes" option in the README will now get a comprehensive MATLAB environment with all essential toolboxes pre-installed, enabling them to work on advanced projects involving machine learning, computer vision, signal processing, and optimization directly in their GitHub Codespace.

The changes follow the existing naming conventions and maintain compatibility with all current devcontainer configurations.

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