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学生对 DeepLearning.AI 提供的 Machine Learning in Production 的评价和反馈

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3,329 个评分

课程概述

In this Machine Learning in Production course, you will build intuition about designing a production ML system end-to-end: project scoping, data needs, modeling strategies, and deployment patterns and technologies. You will learn strategies for addressing common challenges in production like establishing a model baseline, addressing concept drift, and performing error analysis. You’ll follow a framework for developing, deploying, and continuously improving a productionized ML application. Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need experience preparing your projects for deployment as well. Machine learning engineering for production combines the foundational concepts of machine learning with the skills and best practices of modern software development necessary to successfully deploy and maintain ML systems in real-world environments. Week 1: Overview of the ML Lifecycle and Deployment Week 2: Modeling Challenges and Strategies Week 3: Data Definition and Baseline...

热门审阅

RG

Jun 4, 2021

really a great course. It'll really change your way of thinking ML in production use and will help you better understand how can you leverage the power of ML in a way that I'll really create a value

DT

Aug 14, 2021

Excellent course, as always. Very well explain for both Data Sicientist, Software engineer and Manager (with some basics undertsanding of ML). One of these courses that Data Sientist should follow.

筛选依据：

576 - Machine Learning in Production 的 579 个评论（共 579 个）

创建者 Shahzad H

•

Jul 11, 2023

We need more practical graded exercise lab to hone our technical skills, the labs in most cases are easy and not job specific

创建者 Nikita M

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Jul 6, 2025

Useless and boring

创建者 S. H

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Aug 19, 2024

Coursera refuses to issue the specialisation certificate even though I spent over 300 euros and completed all courses. If I was told this beforehand, I would not spend anything on the course. The customer support team has not been helpful.

创建者 Youssef A

•

Dec 10, 2022

too much theory, the course could include some lab practices and be more fun and memorable