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

4.8
stars
49,882 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.

JB

Jul 1, 2020

While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).

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2526 - 2550 of 5,719 Reviews for Structuring Machine Learning Projects

By Steven S

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Nov 17, 2017

Fantastic content and concise easy-to-understand presentation!

By Arushi A

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Oct 7, 2017

good insight to make decisions on how to prioritise ML problem

By Derek C

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Sep 3, 2017

Excellent course, full of really useful advice and techniques.

By Viktor K

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Jul 26, 2021

One thing they don't teach you at universities. Thank you!!!

By scico m

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Feb 19, 2021

awsome but need some coding noteboot as example or assignment

By David J

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Aug 23, 2020

Learned a lot, the instructor has a great presentation style.

By Shihab S

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Jun 19, 2020

Really give you a better understanding over different models.

By - A U S

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May 27, 2020

Very helpful exercises; truly put your learnings to the test.

By Adarsh S

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May 17, 2020

One of the best course to get some insight of the real world.

By GONZALEZ R S

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May 16, 2020

It´s an excellent course about Machine Learning for Beginners

By Pravesh S

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May 13, 2020

Very detailed, and crux. Nobody teaches like this in academia

By Luca P

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Feb 26, 2020

Precious baggage of wise tips to become smarter practitioners

By Ganapathy C

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Dec 30, 2019

Amazing course to start Machine Learning. Thank You Andrew Ng

By haozhiqian

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Oct 3, 2019

Very practical aspects of managing machine learning projects.

By Tuấn L

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Aug 12, 2019

Helpful course with many practical case studies and examples!

By Jummel S

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Jun 30, 2019

This will be really useful for my future projects. Thank you!

By Murat T

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May 12, 2019

Gives you nice insight about optimizing time schedule for ML.

By Li Z

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Mar 10, 2019

I really learned a lot from this course. Thank you very much!

By Vitalii S

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Mar 8, 2019

Good examples and very, very good advices to apply DL systems

By Gaurav A

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Feb 9, 2019

This is one of the most profound courses I have taken so far!

By Khoo T S

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Dec 12, 2018

Great, it helps to build a good deep learning models quickly.

By Pramod K

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Jun 10, 2018

This is a course that is useful for a practicing ML Engineer.

By 김태겸

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May 14, 2018

It is really helpful for building real deep learning systems.

By Valentin A

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Apr 8, 2018

Great course and great advice on how to approach DL projects.

By Saad A

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Nov 2, 2017

Highly recommended to advance ones' career into deep learning