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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....

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YP

Jul 25, 2018

Very important and valuable intuitions about DNN training/optimization. It's full of really practical information while implementing my own models.DNN을 실제 적용할때 반드시 이해하고 적용해야 할 실질적 내용들로 구성된 멋진 코스 입니다!

WG

Mar 18, 2019

Though it might not seem imminently useful, the course notes I've referred back to the most come from this class. This course is could be summarized as a machine learning master giving useful advice.

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4526 - Structuring Machine Learning Projects 的 4550 个评论（共 5,746 个）

创建者 [email protected]

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Jun 16, 2020

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May 30, 2020

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May 28, 2020

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May 10, 2020

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May 4, 2020

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Apr 27, 2020

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Mar 24, 2020

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Jan 9, 2020

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Dec 1, 2019

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Nov 28, 2019

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Nov 7, 2019

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Oct 9, 2019

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Aug 14, 2019

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Aug 6, 2019

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May 23, 2019

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May 18, 2019

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Apr 16, 2019

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Apr 15, 2019

Cool

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Mar 30, 2019

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Feb 13, 2019

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Feb 4, 2019

nice