[AI] Build a Object Recognition App with Python & Angular

所在平台: Udemy

课程主页: https://www.udemy.com/course/ai-python-angular-object-recognition-app/

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课程名称:[AI] 使用 Python 和 Angular 构建物体识别应用 课程概述: 本课程旨在帮助开发者掌握构建尖端 AI 驱动应用的技能,特别是通过 FastAPI、TensorFlow 和 Angular 创建物体识别的全栈 Web 应用。课程讲解了如何融合后端的 Python 和前端的 TypeScript,重点介绍机器学习及计算机视觉的基础知识,为物体识别任务奠定坚实基础。 课程内容包括: 1. **机器学习与计算机视觉的基础**:帮助学生理解 AI 的基本概念,以支持物体识别任务。 2. **FastAPI 框架的探索**:学习如何构建高效可扩展的 REST API,处理请求与数据验证,掌握 Python 的异步编程。 3. **TensorFlow 的实用技术**:参与者将学习如何准备数据集、设计神经网络架构以及优化预训练模型,掌握数据增强、迁移学习和模型评估等技术。 4. **Angular 与 TypeScript 前端开发**:创建动态且响应迅速的用户界面,掌握可重用组件的构建、应用状态管理及实时更新显示物体识别结果。 5. **软件开发最佳实践**:学员将学习如何组织代码和项目结构,利用 Angular 的模块化架构进行有效的应用组织,同时理解 AI Web 应用的部署考虑因素。 通过这门课程,参与者将实际完成一个功能齐全的物体识别 web 应用,获得理论与实践相结合的宝贵经验。无论是希望扩展技能的资深开发者,还是渴望将机器学习模型带到网络上的 AI 爱好者,本课程都提供了实现目标的最佳途径。

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[AI] Create a Object Recognition Web App with Python & AngularBuild AI-driven web apps with FastAPI and Angular. Discover Machine Learning with Python for developers.This comprehensive course, "[AI] Create a Object Recognition Web App with Python & Angular," is designed to empower developers with the skills to build cutting-edge AI-powered applications. By combining the power of FastAPI, TensorFlow, and Angular, students will learn to create a full-stack object recognition web app that showcases the potential of machine learning in modern web development.Throughout this hands-on course, participants will dive deep into both backend and frontend technologies, with a primary focus on Python for AI and backend development, and TypeScript for frontend implementation. The course begins by introducing students to the fundamentals of machine learning and computer vision, providing a solid foundation in AI concepts essential for object recognition tasks.***DISCLAIMER*** This course is part of a 2 applications series where we build the same app with different technologies including Angular, and React. Please choose the frontend framework that fits you best.Students will then explore the FastAPI framework, learning how to create efficient and scalable REST APIs that serve as the backbone of the application. This section will cover topics such as request handling, data validation, and asynchronous programming in Python, ensuring that the backend can handle the demands of real-time object recognition processing.The heart of the course lies in its machine learning component, where students will work extensively with TensorFlow to build and train custom object recognition models. Participants will learn how to prepare datasets, design neural network architectures, and fine-tune pre-trained models for optimal performance. The course will also cover essential topics such as data augmentation, transfer learning, and model evaluation techniques.On the frontend, students will utilize Angular and TypeScript to create a dynamic and responsive user interface. This section will focus on building reusable components, managing application state with services and observables, and implementing real-time updates to display object recognition results. Participants will also learn how to leverage Angular's powerful features such as dependency injection, routing, and reactive forms to create a robust and scalable frontend application.Throughout the course, emphasis will be placed on best practices in software development, including code organization and project structure. Students will explore Angular's modular architecture and learn how to effectively organize their application into feature modules and shared modules. They will also gain insights into deploying AI-powered web applications, considering factors such as model serving, scalability, and performance optimization.By the end of the course, participants will have created a fully functional object recognition web app, gaining practical experience in combining AI technologies with modern web development frameworks. This project-based approach ensures that students not only understand the theoretical concepts but also acquire the hands-on skills necessary to build sophisticated AI-driven applications in real-world scenarios.Whether you're a seasoned developer looking to expand your skill set or an AI enthusiast eager to bring machine learning models to life on the web, this course provides the perfect blend of theory and practice to help you achieve your goals in the exciting field of AI-powered web development using Angular and Python.Cover designed by FreePik

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