Chevron Left
Voltar para Structuring Machine Learning Projects

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

4.8
stars
34,585 classificações
3,616 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.

DC

Mar 08, 2018

Going beyond the technical details, this part of the course goes into the high level view on how to direct your efforts in a ML project. Really enjoyable and useful. Thanks for making this available!

Filtrar por:

326 — 350 de {totalReviews} Avaliações para o Structuring Machine Learning Projects

por Marn Y T

Oct 28, 2019

As a college graduate who took ML classes in college, this course is a lot more useful in terms of developing an intuition toward iterating on ML projects. The interview with Karpathy is the cherry on top :)

por Marco A

Oct 04, 2018

This is a quite different class. It's less math, less formulas but there is so much to learn from the experience of Professor Ng, a whole lot of best practices to follow and tricks to learn. Great contents!

por Dawid D

Aug 09, 2018

Great and unique course! I think that such topics should be a part of any professional ML course.

Having said that, it would be appreciated if the sound volume had higher expected value and lower variance :)

por 李泽帆

Oct 22, 2017

This course gives me an overview sight of the whole process of machine learning project. Not only I know about the technical things, but also know how to structure and point out the position of the project.

por Martin J

Aug 17, 2017

A lot of good thoughts on working with models. I think just getting your hands dirty with some models would help as well. :-) Would be interesting to set up a model to do some difficult tuning exercises.

por Santiago I C

Dec 16, 2018

Un curso que no se encuentra en ningún sitio. Necesario para estructurar proyectos (en todos sitios te enseñan a hacer modelos pero en pocos te enseñan a estructurarlo bien y a saber cómo y en qué mejorar)

por LOS

Dec 12, 2017

Some glitches in the videos, but the content is great. Andrew is an awesome teacher and these are really unique tips coming from his vast experience, it is hard to find similar content elsewhere on the web

por Guilherme

Dec 05, 2017

The discussions on practical guides about designing deep learning systems, dealing with data, bias variance trade-off, and how to organize projects to optimize time usage are much needed for practitioners.

por Terrence G

Oct 12, 2017

Practical advice for new students when tackling a real-world ML project and how to approach to optimize a model's performance. The quizzes provide good examples of use-case scenarios and decisions to take.

por Anurag C

Dec 05, 2019

This course is very helpful to fine tune our machine learning and our deep learning projects and probably more input to the different types of transfer learning examples could have been much more helpful

por Mustafa A

Dec 01, 2019

I love it. it was very helpful but I think if it was an assignment "programming assignment" with some issues "mismatch, incorrect labeling, .. etc " and use those techniques it would be much more helpful.

por Mohamad K

Dec 02, 2018

Its most great and important course ever, please try to listen very carefully to Prof Andrew, he tell you about each and everything you need to become master in ML. Many thanx for Prof Andrew and COURSERA

por Muzammil

May 18, 2019

I believe Andrew Ng shared some key insights into building successful machine learning projects. I really enjoyed the course and believe the shared information to be invalueable for my further research.

por Rajesh C

Oct 16, 2018

This is the most important course of all the machine learning courses from deeplearning.ai. I learned in two weeks, what normally will take years of experience from this course i.e. ML project strategy.

por Govinda N D

Oct 30, 2019

Course is really useful in explaining which part to focus on to reduce the error and how to detect which part of algorithm should be given more time to reduce error and improve performance of algorithm.

por peter b

Sep 03, 2019

A bit more theoretical this time. But the information is worht the time. I think that the knowledge Andrew is spreading will make me more efficient in my AI jobs ahead. At least I hope and think that :)

por Craig M

Dec 06, 2017

Andrew Ng's excellent teaching style leaves you with an intuitive understanding of machine learning setups and potential pitfalls. For me it's the best way to learn; this stuff really sticks in my head!

por Wilem

Nov 24, 2019

Really interesting!

We used to be concerned about unbalanced train/dev/test, and with this course I realised this are not the main problems for achieving performance in ML

A master class.

Thanks Andrew!

por William G

Jul 14, 2019

not as technical as the first 2 courses in this specialization (and the next 2 for that matter), but it is still a well rounded course and highly recommend to do all the courses in this specialization!

por Karthik V

Sep 12, 2018

Extremely interesting and useful practical advice that can help make significant difference when thinking about how to identify and correct problems. The quizzes were fantastic and made me think a lot.

por Ernesto N S

Dec 04, 2017

Excellent material. I would say this is the most important course of this specialization. Knowing how to approach a certain problem can indeed save us a lot of time and help us avoid a lot of mistakes.

por Wonjin K

Oct 01, 2017

This course gives great intuitions to develop deep learning model and how to go with deep learning project. I was really impressed and felt like I gain a real experiences without working at industries.

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.