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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/create-machine-learning-models-in-microsoft-azure
课程评论：没有评论
课程名称：在 Microsoft Azure 中创建机器学习模型 课程概述：机器学习是预测建模和人工智能的基础。本课程旨在帮助您理解机器学习的核心概念，并使用常见的机器学习工具构建模型。您将学习如何在 Azure 环境中规划和创建数据科学工作负载，运行数据实验，以及训练、管理、优化和部署机器学习模型。 课程内容涵盖从基本的经典机器学习模型到探索性数据分析及定制架构。课程以易于理解的概念内容和互动式 Jupyter 笔记本引导学习，适合对机器学习有一定了解或数学基础扎实的学习者。课程还介绍了流行工具如 scikit-learn、TensorFlow 和 PyTorch 的应用，让您对 Azure ML 或 Azure Databricks 的机器学习示例有基本的了解。此外，课程也为希望进一步学习深度学习和神经网络的学员打下基础。 该课程包含五个模块，旨在为参加 DP-100 认证考试做准备，该考试评估您在 Azure 机器学习上操作机器学习解决方案的能力。每个模块教授与考试相关的概念和技能，帮助您在 Microsoft Azure 上进行数据采集、准备、模型训练与部署，以及机器学习解决方案监控。 课程大纲： 1. 探索数据并创建预测数值的模型 - 学习如何使用 Python 进行数据探索、可视化和处理，并应用回归模型预测数值。 2. 训练和评估分类与聚类模型 - 学习如何使用分类算法创建预测类别的机器学习模型，以及使用聚类算法创建无监督机器学习模型。 3. 训练和评估深度学习模型 - 学习深度学习的基本原理，使用 PyTorch 或 TensorFlow 创建深度神经网络模型，以及使用卷积神经网络进行图像分类。 这个课程不仅提供了机器学习的基础知识，还为您在云端实现机器学习解决方案的深入理解做好了准备。
Name:Explore data and create models to predict numeric values
Description:Data exploration and analysis is at the core of data science. Data scientists require skills in languages like Python to explore, visualize, and manipulate data. In this module, you will learn how to use Python to explore, visualize, and manipulate data. You will also learn how regression can be used to create a machine learning model that predicts numeric values. You will use the scikit-learn framework in Python to train and evaluate a regression model.
Name:Train and evaluate classification and clustering models
Description:Classification is a kind of machine learning used to categorize items into classes. In this module, you will learn how classification can be used to create a machine learning model that predicts categories, or classes. You will use the scikit-learn framework in Python to train and evaluate a classification model. You will also learn how clustering can be used to create unsupervised machine learning models that group data observations into clusters. You will use the scikit-learn framework in Python to train a clustering model.
Name:Train and evaluate deep learning models
Description:In this module, you will learn about the fundamental principles of deep learning, and how to create deep neural network models using PyTorch or Tensorflow. You will also explore the use of convolutional neural networks to create image classification models.
Machine learning is the foundation for predictive modeling and artificial intelligence. If you want to learn about both the underlying concepts and how to get into building models with the most common machine learning tools this path is for you. In this course, you will learn the core principles of machine learning and how to use common tools and frameworks to train, evaluate, and use machine learning models. This course is designed to prepare you for roles that include planning and creating a suitable working environment for data science workloads on Azure. You will learn how to run data experiments and train predictive models. In addition, you will manage, optimize, and deploy machine learning models into production. From the most basic classical machine learning models, to exploratory data analysis and customizing architectures, you’ll be guided by easy -to-digest conceptual content and interactive Jupyter notebooks. If you already have some idea what machine learning is about or you have a strong mathematical background this course is perfect for you. These modules teach some machine learning concepts, but move fast so they can get to the power of using tools like scikit-learn, TensorFlow, and PyTorch. This learning path is also the best one for you if you're looking for just enough familiarity to understand machine learning examples for products like Azure ML or Azure Databricks. It's also a good place to start if you plan to move beyond classic machine learning and get an education in deep learning and neural networks, which we only introduce here. This program consists of 5 courses to help prepare you to take the Exam DP-100: Designing and Implementing a Data Science Solution on Azure. The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at cloud scale using Azure Machine Learning. This specialization teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure . Each course teaches you the concepts and skills that are measured by the exam.
