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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practical-arduino-and-cnn-examples-for-beginners-in-c/
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**课程名称：** 使用 Arduino/CNN 实战精通 C++ **课程概述：** 本课程是一门全面深入的 C++、Arduino 及机器学习、深度学习实战指南。课程旨在帮助学习者建立坚实的理论基础，并通过 LibTorch（PyTorch 的 C++ API）和 C++ 进行实际应用操作。 **学习内容：** * **C++ 和 Arduino 入门：** 面向初学者或需要巩固基础的学习者，从 C++ 编程基础到 Arduino 的使用和编程，循序渐进，打下扎实基础。 * **机器学习与深度学习导论：** 掌握机器学习、深度学习及神经网络的基础概念。 * **卷积神经网络 (CNN)：** 理解卷积层、池化层和全连接层，并使用 PyTorch 构建 CNN 模型。 * **LibTorch 实战：** 学习数据加载、预处理、CNN 模型训练、评估与优化。 * **Arduino 集成：** 深入了解 Arduino、设备端 AI、边缘计算，以及如何在 Arduino 上部署 LibTorch 模型，实现实时机器学习和硬件环境下的模型测试。 * **CNN 训练与测试：** 学习在数据集上训练和测试 CNN 的流程。 * **模型导出 (LibTorch 和 ONNX)：** 掌握将训练好的 LibTorch 模型导出，并转换为 ONNX 格式的方法。 * **C++ 中加载和使用模型：** 学习在 C++ 环境中加载导出的 ONNX 模型并进行推理。 * **C++ 代码优化：** 学习提高 C++ 代码性能的各种策略。 * **进阶主题：** 探索高级 CNN 架构及其在 LibTorch 中的实现。 **课程结构：** 课程共分为九大模块，内容涵盖了从基础到高级的 C++、Arduino 和深度学习应用。
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 learnThe book is structured into nine distinct modules: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.Introduction to Machine Learning and Deep Learning - Acquire the basics of Machine Learning, Deep Learning, and Neural Networks.Convolutional Neural Networks - Comprehend Convolutional Layers, Pooling, and Fully Connected Layers. Construct a CNN using PyTorch.Practical Implementation with LibTorch - Gain knowledge about Data Loading, Preprocessing, Training a CNN Model, and Model Evaluation and Optimization.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.Training and Testing the CNN - Understand the procedure of training and testing a Convolutional Neural Network (CNN) on a dataset.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.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.Optimizing C++ Code - Discover various strategies to optimize the C++ code for enhanced performance.Advanced Topics - Learn about advanced CNN architectures and their implementation using LibTorch.Table of ContentsIntroduction to C++ and ArduinoIntroduction to Machine Learning and Deep LearningConvolutional Neural NetworksPractical Implementation with LibTorchIntegration with ArduinoTraining and Testing the CNNExporting the Trained Model in LibTorch and ONNXLoading and Using the Model in C++Optimizing C++ CodeAdvanced Topics
