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Learner Reviews & Feedback for Structuring Machine Learning Projects by DeepLearning.AI

4.8
stars
49,903 ratings

About the Course

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....

Top reviews

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.

TG

Dec 1, 2020

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

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2676 - 2700 of 5,721 Reviews for Structuring Machine Learning Projects

By Chenxi G

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Aug 8, 2018

Some of the assignment questions are a little ambiguous.

By Steven L

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Jun 22, 2018

Very good/unique insights into applied machine learning.

By Itrat R

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Jun 11, 2018

Fantastic Course!!! Deserves nothing less than 5 star!!!

By Subramaniam V

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Jun 6, 2018

Really useful set of principles to guide any ML project.

By Yuri V H V

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Jan 2, 2018

great course, it is the basic recipe of machine learning

By Jorge D P

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Nov 19, 2017

Quite more useful than it seemed. A must, don't miss it.

By Aaron D

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Nov 13, 2017

Really helpful for moving forward a concrete ML project.

By Noam D

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Sep 3, 2017

Great course, lots of practical information and insights

By LEE C T

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Nov 22, 2020

it provides practical tips on applying machine learning

By Kunal K

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Jun 28, 2020

Thank you, this helped develop problem solving mindset.

By Henry D

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Jun 26, 2020

Excellent and practical course. Provide very good tips.

By Krishna P D

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Jun 24, 2020

Great practical insights on structuring AI, DS projects

By Marc M

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May 6, 2020

Muy bueno y util si te estas iniciando en Deep Learning

By EC-A-411 S V

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Apr 8, 2020

I have gain tons of knowledge by spending grams of time

By Priyam S

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Aug 27, 2019

very insightful and relatable to industrial environment

By Alexander R M

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May 7, 2019

You need to take this course to get the bigger picture!

By ken A B

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Oct 25, 2018

outstanding advice within the videos and simulations...

By Hamidreza F

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Aug 13, 2018

Really Helpful for managing the deep learning projects.

By Alexander L

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Jul 22, 2018

a lot of real world questions are explained! awesome!!!

By Pankaj S

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Apr 15, 2018

Undoubtedly the most practical course....Thanks a lot..

By Alexander G

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Mar 31, 2018

Thank's a lot for numerous useful tricks and methodics!

By Wurihan

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Mar 25, 2018

I thought I learnt about engineering theory on projects

By Malek B

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Mar 16, 2018

Amazing courses thank you Andrew and all coursera team.

By brightmart

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Mar 14, 2018

single value metric+dev set let us focus on our target.

By Héctor C

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Nov 22, 2017

This is the course of the program that MAKES YOU THINK.