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

4.8
stars
49,631 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.

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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2651 - 2675 of 5,688 Reviews for Structuring Machine Learning Projects

By ruchi m p

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Jul 29, 2021

Very good explanation and best practices has been shared

By Moritz K

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Jan 10, 2021

As usual a really nicely structured course by Andrew Ng!

By induraj

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Jun 6, 2020

Exceptional Course. Thank you Professor Andrew and team.

By Syed T S

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May 21, 2020

As usual Andrew NG at his best. Very informative course.

By Timur B

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Jul 11, 2019

Lots of useful advice on how to proceed with ML projects

By John H

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Jul 11, 2019

excellent class and I especially like Andrew's teaching.

By Naman S

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Jul 4, 2019

A must course for anyone who is studying deep learning .

By Ivan M

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May 24, 2019

Important topics that everybody skipped, awesome course!

By Satheeshkumar M

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May 4, 2019

Great course to learn practical nuances of Deep Learning

By Tan B

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Feb 14, 2019

Very good tips on how to fix/improve the training model.

By dmitry p

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Jan 9, 2019

Useful course for high level DNN management and planning

By Alexander O

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Dec 29, 2018

Terrific content, well-structured and explained clearly.

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