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Comentários e feedback de alunos de Structuring Machine Learning Projects da instituição deeplearning.ai

4.8
stars
34,667 classificações
3,623 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

AM

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.

WG

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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351 — 375 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Antony W

Jul 17, 2019

I am glad I took this class. There are a lot of things think about with respect to structuring your M/L project. Fortunately, it is not as mysterious as people often claim...but it is very nuanced.

por Yong H P

Jul 26, 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!

por 翁嘉进

Apr 07, 2018

It is a special lesson that guide me to think how to build a good model for ML. There is no doubt that Andrew ng taught his project experience without exception and hope that we can benefit from it.

por Amey N

Nov 12, 2019

The course gives a sound intuition and insight into the parameters to be considered and the crucial thought process involved in making the decisions for improving the performance of neural networks.

por Anshu S P

Jun 21, 2019

Really a good course with mostly the theoretical knowledge on some aspects to reuse your model as well as some error analysis. Thoroughly taught with lots of real-life examples, thanks to Andrew Ng.

por Young L

Nov 29, 2017

It's a great course! This course gave me a lot of new perspectives in constructing a machine learning project. Especially, the discussion of data distribution in the train/dev/test set is fantastic.

por Chitra V

Jan 10, 2019

Interesting course especially for ML novices. A short course and could be completed quickly, however, one needs to carefully review the lectures to avoid missing key points. Well-structured course!

por Arvind S

Mar 03, 2019

While there are lots of techniques out there, this course really helps you gain a different perspective on the bigger picture and teaches you to avoid some of the common pitfalls you may encounter

por Max B

Nov 21, 2018

Fantastic! As is pointed out by Andrew Ng, the material is not taught in other courses. You will get answers for a lot of things you might have wondered when working on a machine learning project.

por Ramón R

Mar 30, 2018

Shorter than other courses in this specialization, but realy important. It helps to structure machine learning projects to shorten the time and effort and to prioritize the different alternatives.

por Sunne K

Oct 04, 2017

Very insightful thoughts from an expert and legend in Deep Learning and ML. Well explained and easy to digest the information. Keep up the excellent work Andrew and thank you for your hard work!

por Samuel d Z

Mar 18, 2018

Fascinating insights how to solve issues in ML projects. Saves lot of time if you have to find out yourself. Great share of experience and very appealing and practical examples, easily explained.

por Ytsen d B

Aug 16, 2017

This was very insightful.

No rocket science, but taking to heart these lessons may save you and your team months of work.

Pragmatic way of thinking about getting your deep learning project to work.

por Yi C

Sep 09, 2019

I made detail notes for courses in this specialization. The supplemental notes in this course helped so much for me to save time making notes. If I can give 6 stars, I will. Thank you very much.

por Ashutosh K

Aug 21, 2018

This course is extremerly useful for being successful and efficient in a machine learning project. I'll highly recommend this course to take if you want to speed up your ML project and research.

por Arun R

Mar 26, 2018

This is a very unique course! Nowhere else is practical ML covered in so much detail. Many of the questions I struggled when doing ML are addressed in this course in a very clear manner. Thanks!

por Nitin

Jan 15, 2018

Please include more of programming. Until this course I have a decent idea of strategies for deep learning but still I am not sure if I can actually apply them that well to build a decent model.

por David C

Dec 16, 2017

Ce cours permet de donner un retour d'expérience sur des projets de Deep Learning réels, et nous confronte à la réalité des difficultés quotidiennes que les acteurs de ce domaine ont a résoudre.

por Ian C

Oct 22, 2017

It's great to learn the theory, and it's a great expansion to the earlier courses. It's slightly less fun not being able to do the coding course work. As ever phenomenal lectures from Andrew Ng.

por Sudipto K

Aug 16, 2017

Amazing course contents and case studies to get a solid understanding of key Deep learning concepts and applications in real world scenarios...very helpful for freshers in Deep Learning like me.

por Felipe S F

Dec 01, 2019

Learning how to better deploy and analyze Machine Learning issues has helped me a lot in understanding the issues and finding solutions for my thesis project, in machine vision for agriculture.

por Lim K Z

Jan 22, 2019

I like the "flight simulator". Excellent scenario-based training. I also like one of Ruslan's advice - code the backprop of CNN from scratch to really understand deep learning. Keep it up :)

por Weinan L

Feb 13, 2018

This is the most down-to-early and hand-to-hand course of the whole series so far. For real world projects tuning, this course may save you months of efforts and tons of cost. Highly recommend!

por Bryan W

Jan 22, 2018

Taught a lot of tools for tweaking the NN in a comprehensive ways. This course makes me want to jump right in and practice all those tools available (even without programming exercise provided)

por Adnan B

Dec 28, 2017

Great course underlining that one should think first and then implement. It also helps to understand where to put the effort when we face real-world AI challenges. Thank you guys, great course!