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所在平台: Udemy |
课程主页: https://www.udemy.com/course/ai-for-engineering-applications-a-z/
课程评论：没有评论
Coursera 上的“面向工程的机器学习：A-Z”课程将为您在工程应用中使用机器学习做好充分准备。本课程涵盖机器学习的各个方面，重点介绍了四种核心机器学习类型：优化、结构化数据、强化学习和机器视觉。 您将学习**机器学习算法背后的数学原理，并从头开始编写和构建这些算法**。课程还将指导您如何**为图像、强化学习、结构化数据和优化预处理数据，以及分析数据以提取有价值的见解，并熟练使用开源库**。 具体内容包括： * **优化**：学习优化基础，从头构建优化算法，并使用 Google OR Tools 解决车间作业问题。 * **结构化数据**：掌握结构化数据处理算法，使用 K-Nearest Neighbors 从头构建数据聚类，并通过 scikit-learn 等库实现飞机发动机剩余使用寿命预测（预测性维护）。 * **强化学习**：理解强化学习原理，从头构建 Q-Table 算法，并使用 Keras 和 Stable Baselines 库控制室温，以及通过 OpenAI Gym 构建自定义环境。 * **深度学习和机器视觉**：深入了解深度学习基础和用于机器视觉检查的网络，利用 TensorFlow/Keras 构建深度神经网络，处理图像进行分类（有裂纹和无裂纹图像），以及使用 U-Net 进行裂纹检测和分割（勾勒出每张图像中的裂纹位置）。 即使您没有机器学习或计算工程方面的经验，本课程也适合您。它全面而简洁，从机器学习基础知识到使用真实数据和强大的开源库进行实际应用，旨在满足企业在工程应用中应用机器学习的需求，创造更智能的未来工程产品。
DescriptionThis is a complete course that will prepare you to use Machine Learning in Engineering Applications from A to Z. We will cover the fundamentals of Machine Learning and its applications in Engineering Companies, focusing on 4 types of machine learning: Optimization, Structured data, Reinforcement Learning, and Machine Vision.What skills will you Learn:In this course, you will learn the following skills:Understand the math behind Machine Learning Algorithms.Write and build Machine Learning Algorithms from scratch.Preprocess data for Images, Reinforcement learning, structured data, and optimization.Analyze data to extract valuable insights.Use opensource libraries.We will cover:Fundamentals of Optimization and building optimization algorithms from scratch.Use Google OR Tools optimization library/solver to solve Shop job problems.Fundamentals of Structured Data processing algorithms and building data clustering using K-Nearest Neighbors algorithms from scratch.Use scikit-learn library along with others to predict the Remaining Useful Life of Aircraft Engines (Predictive maintenance).Fundamentals of Reinforcement Learning and building Q-Table algorithms from scratch.Use Keras & Stable baselines libraries to control room temperature and construct a custom-made Environment using OpenAI Gym.Fundamentals of Deep Learning and Networks used in deep learning for machine vision inspection.The use of TensorFlow/ Keras to construct Deep Neural Networks and process images for Classification using CNN (images that have cracks and images that do not) and crack Detection and segmentation using U-Net (outline the crack location in every crack image).If you do not have prior experience in Machine Learning or Computational Engineering, that's no problem. This course is complete and concise, covering the fundamentals of Machine Learning followed by using real data with strong opensource libraries needed to apply AI in Companies. Let's work together to fulfill the need of companies to apply Machine Learning in Engineering applications to MAKE OUR FUTURE ENGINEERING PRODUCTS SMARTER.
