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Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição

33,506 classificações
3,516 avaliações

Sobre o curso

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn from my experience building and shipping many deep learning products. This course also has two "flight simulators" that let you practice decision-making as a machine learning project leader. This provides "industry experience" that you might otherwise get only after years of ML work experience. After 2 weeks, you will: - Understand how to diagnose errors in a machine learning system, and - Be able to prioritize the most promising directions for reducing error - Understand complex ML settings, such as mismatched training/test sets, and comparing to and/or surpassing human-level performance - Know how to apply end-to-end learning, transfer learning, and multi-task learning I've seen teams waste months or years through not understanding the principles taught in this course. I hope this two week course will save you months of time. This is a standalone course, and you can take this so long as you have basic machine learning knowledge. This is the third course in the Deep Learning Specialization....

Melhores avaliações


Nov 23, 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.


Mar 19, 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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251 — 275 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Lin Z

Mar 29, 2019

very good guidance on how to start a machine learning project, including many interesting discussions including how to choose the size of training/test/dev set, how to analyze the errors, how to deal with mismatched distributions of test/traning/dev set by adding a training_dev set and how to do end-to-end and multitask training. The contents are well exercised by two well defined case studies.

por Mathew S

Mar 29, 2019

Excellent high level discussions. I am thankful I completed this course before getting too deep into my current deep learning project.

por Bharat S H

Mar 30, 2019

I hope my mentor will live for thousand years. The world needs person like you. I have learnt a lot. Confidence as an machine learning engineer is increasing day by day.Thanks a lot Professor.

por Zigmond V L

Mar 29, 2019

Good, practical information to help tackle ML projects most effectively.

por Sergei S

Apr 01, 2019

Among other courses of this series, this course brings up some of the most important things every (deep learning) scientist should be aware of.

por Muhammad H B K

Apr 02, 2019

It was an amazing experience. Thankyou Professor Andrew and Team

por Kartik g

Apr 01, 2019

Its quite informative

por Ravish R

Apr 01, 2019

Nice course for getting a feel of error.

por Haoqiu W

Mar 31, 2019

nice teacher

por Rory M

Apr 01, 2019

Great course - it was a nice change of pace to have a higher-level view of the processes involved.

por Erick A

Mar 31, 2019

This is a very very interesting course since it discusses a lot of subtleties one deals with when developing machine learning projects

por Wei L

Apr 02, 2019


por Nemanja J

Apr 03, 2019

you are the best, this should be referent point of presenting knowledge

por Arun R

Apr 03, 2019

Amazing it was.

por Karel N N

Apr 05, 2019

Excellent courses, and a great teacher! Best regards and thank you very much!

por Van N H P

Apr 05, 2019

This course is amazing. These material is so unique to this course and it's hard to find else where.

por Lien C

Apr 04, 2019

Great practical insights of how to start a ML project, how to improve/optimize the system, how to identify and troubleshoot common problems in deep learning. The course provides comprehensive high level guidelines for anyone who uses machine learning, even without having any programming experience!

por Federico A G C

Apr 05, 2019

Surpassing Coursera level performance

por ChenTianyi

Apr 07, 2019


por Aparup B

Apr 06, 2019

By far the best of this series. These kind of accumulated lessons are very rare.

por Bassel G

Apr 08, 2019

A grate course and the grate prof.

por Saurabh S

Apr 08, 2019

Really helpful course. Lots of information on how should you drive your machine learning project.

por Kelvin G

Mar 28, 2019

Andrew NG impressive. As always

por Sergio L M

Mar 28, 2019


por Marilson C

Mar 28, 2019

Great course.