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学生对 deeplearning.ai 提供的 Structuring Machine Learning Projects 的评价和反馈

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课程概述

In the third course of the Deep Learning Specialization, you will learn how to build a successful machine learning project and get to practice decision-making as a machine learning project leader. By the end, you will be able to diagnose errors in a machine learning system; prioritize strategies for reducing errors; understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance; and apply end-to-end learning, transfer learning, and multi-task learning. This is also a standalone course for learners who have basic machine learning knowledge. This course draws on Andrew Ng’s experience building and shipping many deep learning products. If you aspire to become a technical leader who can set the direction for an AI team, this course provides the "industry experience" that you might otherwise get only after years of ML work experience. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

热门审阅

AM

Nov 22, 2017

I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.

MG

Mar 30, 2020

It is very nice to have a very experienced deep learning practitioner showing you the "magic" of making DNN works. That is usually passed from Professor to graduate student, but is available here now.

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226 - Structuring Machine Learning Projects 的 250 个评论(共 5,543 个)

创建者 Dunitt M

Feb 10, 2019

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Sep 7, 2017

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Aug 13, 2020

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Nov 19, 2018

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Jan 3, 2021

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Oct 24, 2018

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Feb 25, 2018

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Dec 29, 2019

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Sep 4, 2017

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Feb 28, 2019

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Oct 29, 2017

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Jul 9, 2020

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May 18, 2019

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Mar 31, 2020

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Jan 16, 2022

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May 14, 2021

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Jan 4, 2021

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Mar 8, 2020

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Sep 11, 2017

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Sep 6, 2018

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Mar 16, 2018

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Oct 12, 2017

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Jul 15, 2020

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Jun 3, 2020

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Oct 22, 2020