C++ for Beginners: Create Real-World Projects with Arduino and CNN
Embark on a journey into the world of Machine Learning, Deep Learning, C++, and Arduino with this comprehensive guide. This book is meticulously crafted to provide a robust understanding of the fundamental concepts and hands-on experience with practical implementation using LibTorch (the PyTorch C++ API) and C++.
The book begins with an introductory course on C++ and Arduino, designed for beginners and those looking to refresh their knowledge. This course covers everything from the basics of programming in C++ to the intricacies of working with Arduino, all taught from scratch. It provides a solid foundation for the subsequent modules.
What you will learn
The book is structured into nine distinct modules:
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Introduction to C++ and Arduino – This module serves as an introductory course for beginners. It covers the basics of programming in C++, the use of Arduino IDE, and the fundamentals of Arduino programming.
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Introduction to Machine Learning and Deep Learning – Acquire the basics of Machine Learning, Deep Learning, and Neural Networks.
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Convolutional Neural Networks – Comprehend Convolutional Layers, Pooling, and Fully Connected Layers. Construct a CNN using PyTorch.
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Practical Implementation with LibTorch – Gain knowledge about Data Loading, Preprocessing, Training a CNN Model, and Model Evaluation and Optimization.
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Integration with Arduino – Delve into Arduino, On-device AI, Edge Computing, and the process of deploying a LibTorch Model on Arduino. Understand the potential of Arduino in facilitating real-time machine learning applications and how it can be used to implement and test machine learning models in a hardware environment.
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Training and Testing the CNN – Understand the procedure of training and testing a Convolutional Neural Network (CNN) on a dataset.
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Exporting the Trained Model in LibTorch and ONNX – Learn the method to export a trained LibTorch model and convert it into the Open Neural Network Exchange (ONNX) format.
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Loading and Using the Model in C++ – Learn the technique to load the exported ONNX model in a C++ environment and use it for inference.
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Optimizing C++ Code – Discover various strategies to optimize the C++ code for enhanced performance.
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Advanced Topics – Learn about advanced CNN architectures and their implementation using LibTorch.
Table of Contents
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Introduction to C++ and Arduino
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Introduction to Machine Learning and Deep Learning
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Convolutional Neural Networks
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Practical Implementation with LibTorch
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Integration with Arduino
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Training and Testing the CNN
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Exporting the Trained Model in LibTorch and ONNX
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Loading and Using the Model in C++
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Optimizing C++ Code
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Advanced Topics
Course Details
- Language: #English
- Students: 1800
- Rating: 4.0 / 5.0
- Reviews: 1
- Category: #IT_and_Software
- Published: 2023-07-14 03:15:24 UTC
- Price: €19.99
- Instructor: | | okeke maryclare | |
- Content: 1 total hour
- Articles: 3
- Downloadable Resources: 0
Coupon Details
- Coupon Code: E311896F1F41793E885F
- Expire Time: 2024-05-30 06:53:00 UTC