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所在平台: Udemy |
课程主页: https://www.udemy.com/course/hands-on-machine-learning-for-net-developers/
课程评论：没有评论
课程名称: .NET开发者实践机器学习 课程概述: 本课程旨在帮助.NET开发者利用他们的技能，轻松将机器学习集成到几乎所有的.NET应用程序中。您将学习如何使用微软的新机器学习库ML.NET实施机器学习并构建模型。课程内容覆盖如何有效利用该库将机器学习构建并集成到.NET应用程序中。 学习内容包括： - 使用ML.NET库实现各种机器学习任务和算法。 - 使用Model Builder和命令行接口（CLI）通过自动机器学习（AutoML）构建自定义模型。 - 加载和准备数据以训练和评估模型。 - 在经过训练的模型上进行预测，并进行模型的再训练。 - 涉及图像分类、情感分析、推荐引擎等多个应用场景。 - 探索提升模型性能和准确性的技巧。 - 通过迁移学习在ML.NET应用中利用预训练的TensorFlow模型扩展ML.NET。 通过本课程的学习，即使您之前对机器学习没有任何知识，您也将能够自信地执行机器学习任务，并使用ML.NET库构建自定义机器学习模型。 作者介绍: 本课程由Karl Tillström主讲，他一直对编程如何实现惊人事物充满热情。自2007年参加第一堂人工神经网络课程以来，Karl对机器学习进行了大量实验。他拥有超过15年的.NET专业经验，作为软件工程师和系统架构师，参与构建了从航空公司移动值机系统到在线支付系统的多种系统。Karl在瑞典查尔姆斯理工大学获得了计算机科学与工程的硕士学位，进一步提高了他的专业知识。
ML.NET enables developers utilize their.NET skills to easily integrate machine learning into virtually any.NET application. This course will teach you how to implement machine learning and build models using Microsoft's new Machine Learning library, ML.NET. You will learn how to leverage the library effectively to build and integrate machine learning into your.NET applications.By taking this course, you will learn how to implement various machine learning tasks and algorithms using the ML.NET library, and use the Model Builder and CLI to build custom models using AutoML.You will load and prepare data to train and evaluate a model; make predictions with a trained model; and, crucially, retrain it. You will cover image classification, sentiment analysis, recommendation engines, and more! You'll also work through techniques to improve model performance and accuracy, and extend ML.NET by leveraging pre-trained TensorFlow models using transfer learning in your ML.NET application and some advanced techniques.By the end of the course, even if you previously lacked existing machine learning knowledge, you will be confident enough to perform machine learning tasks and build custom ML models using the ML.NET library.About the AuthorKarl Tillström has been passionate about making computers do amazing things ever since childhood and is strongly driven by the magic possibilities you can create using programming. This makes advances in machine learning and AI his holy grail; since he took his first class in artificial neural networks in 2007, he has experimented with machine learning by building all sorts of things, ranging from Bitcoin price prediction to self-learning Gomoku playing AI.Karl is a software engineer and systems architect with over 15 years' professional experience in.Net, building a wide variety of systems ranging from airline mobile check-ins to online payment systems.Driven by his passion, he took a Master's degree in Computer Science and Engineering at the Chalmers University of Technology, a top university in Sweden.
