Deep Learning with MATLAB and Python– From Training to Edge Deployment: Implementing PyTorch, YOLO v8, and Transformer Models for Computer Vision and Signal Processing

 

Deep learning is reshaping the way machines perceive the world — from recognizing objects in images to interpreting signals in real time. But with the landscape constantly evolving, developers and engineers need guidance that goes beyond theory. They need practical workflows, real tools, and actionable techniques that work in real environments.

Deep Learning with MATLAB and Python – From Training to Edge Deployment answers this need by providing a hands-on, end-to-end roadmap for building deep learning systems that are not only powerful but also deployable on real devices. By combining the strengths of MATLAB and Python, this book helps you tackle real problems in computer vision, signal processing, and embedded AI — with tools like PyTorch, YOLO v8, and transformer models.

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🌟 Why This Book Matters

Most deep learning resources stop at model training — often focused on desktops or cloud servers. But building practical intelligent systems today means thinking about the entire pipeline, including:

• data preparation and training

• model optimization

• cross-platform integration

• real-world deployment

• edge devices and resource-constrained systems

This book bridges that gap by teaching not only how models are trained but also how they are made useful — from Python research workflows to practical MATLAB workflows and finally to deployment on edge devices.

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📘 What You’ll Learn

Here’s a breakdown of the core knowledge this book equips you with:

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🧠 1. Deep Learning Fundamentals

The book begins by grounding you in the basics — but not as dry theory:

• neural network architecture

• activation functions

• loss and optimization

• training workflows in PyTorch and MATLAB

These fundamentals are essential whether you’re building vision systems or signal analysis pipelines.

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🐍 2. Training with Python & PyTorch

Python remains the most widely used language for deep learning — and PyTorch is one of the most flexible and powerful frameworks. The book walks you through:

• building and training deep learning models

• implementing convolutional neural networks (CNNs)

• experimenting with transformer architectures

• tuning and debugging training workflows

You’ll learn how to use PyTorch to prototype and iterate quickly — a key skill in modern AI development.

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🧠 3. Computer Vision with YOLO v8

Object detection is one of the most in-demand deep learning applications today. With YOLO (You Only Look Once) v8, you’ll learn how to:

• build high-speed detection systems

• apply model pruning and optimization

• train custom datasets for object recognition

• integrate detection pipelines into real apps

YOLO v8’s speed and accuracy make it ideal for robotics, surveillance, autonomous systems, and more.

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🔄 4. Transformers and Signal Processing

Transformers aren’t just for language — they are now transforming vision and signal analysis too. The book shows how transformer models can be used for:

• time series and signal classification

• sequence modeling for non-images

• combining sequential and spatial reasoning

This expands your deep learning toolkit beyond traditional CNN models.

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🛠 5. MATLAB for Deep Learning Workflows

MATLAB offers powerful support for numerical computing, visualization, and embedded systems. In this book, you’ll learn how to:

• use MATLAB for data preparation and visualization

• integrate trained networks into MATLAB workflows

• prototype models for engineering and scientific use cases

• leverage MATLAB tools for deployment and simulation

This dual-language approach gives you flexibility: the research agility of Python + PyTorch and the engineering strength of MATLAB.

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🚀 6. Deployment to Edge and Embedded Systems

Theory is only half the challenge — deployment is where many projects stall. This book prepares you to:

• optimize models for resource-limited hardware

• convert models for deployment on microcontrollers and FPGAs

• build efficient inference pipelines

• handle quantization, pruning, and hardware acceleration

Whether you’re targeting IoT devices, automation systems, or embedded AI chips — you’ll learn the techniques that make deep learning practical outside the lab.

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🛠 Real-World Focus — Not Just Theory

What sets this book apart is its applied approach:

• Clear workflows that move from idea to working system

• Dual-language examples for Python and MATLAB

• Practical use cases in vision and signal domains

• Edge deployment techniques developers actually need

This combination makes it valuable for engineers, AI developers, researchers, and students who want to build and ship real solutions.

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💡 Who Should Read This Book

This book is ideal if you are:

✔ A developer or engineer building AI systems
✔ A data scientist bridging research and production
✔ A student entering the deep learning and AI field
✔ A professional deploying models on edge hardware
✔ Someone curious about both Python and MATLAB workflows

You don’t need decades of experience — just a willingness to learn and apply concepts step-by-step.

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Hard Copy: Deep Learning with MATLAB and Python– From Training to Edge Deployment: Implementing PyTorch, YOLO v8, and Transformer Models for Computer Vision and Signal Processing

Kindle: Deep Learning with MATLAB and Python– From Training to Edge Deployment: Implementing PyTorch, YOLO v8, and Transformer Models for Computer Vision and Signal Processing

✨ Final Thoughts

Deep Learning with MATLAB and Python – From Training to Edge Deployment is more than a book — it’s a toolkit for practical AI building. By combining Python and MATLAB workflows with cutting-edge models like YOLO v8 and transformers, it gives you both flexibility and depth.

Whether you’re interested in computer vision, signal analysis, or building AI that runs on real devices, this book equips you with the skills and confidence to go from concept to deployment.

If your goal is to build deep learning systems that work in the real world, this book is a powerful companion on that journey.