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Structuring Machine Learning Projects(으)로 돌아가기

deeplearning.ai의 Structuring Machine Learning Projects 학습자 리뷰 및 피드백

4.8
별점
38,546개의 평가
4,216개의 리뷰

강좌 소개

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....

최상위 리뷰

MG

Mar 31, 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.

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.

필터링 기준:

Structuring Machine Learning Projects의 4,181개 리뷰 중 3651~3675

교육 기관: 蕭博偉

Jan 13, 2020

Briefly share Andrew's experience for directing what to do next in a ML project.

교육 기관: Jarno R

Sep 11, 2019

Extremely valuable practical information regarding how to structure ML projects.

교육 기관: Onkar M

Jun 11, 2019

This is a very interesting course but yes this is totally theoretical in nature.

교육 기관: Thomas P

Sep 21, 2017

Good high-level course on how to think about projects implementing Deep Learning

교육 기관: Nicolo d G

Feb 17, 2019

A bit short and light to be a course on its own but still useful in the series.

교육 기관: Jose L M

Oct 02, 2018

Quiz answers were not that clear. They seem more "gotcha" than "deep learning".

교육 기관: Sumesh R

Apr 09, 2018

It would be good to have more practical/industry scenarios added to the course.

교육 기관: Victor P

Nov 10, 2017

Always great, but some little issues in the content makes it feel less perfect.

교육 기관: Francesco D Z

Sep 25, 2017

Great class overall. Some practice example on multi-task would have been nice.

교육 기관: Steve D

May 10, 2020

Great course for a coding professional to improve on their fine tuning skills

교육 기관: Maik F

Apr 01, 2019

Greate knowledge, but I had a hard time motivating myself through this theroy

교육 기관: José A M

Aug 05, 2018

Good background theory for people starting in the field to get familiar with.

교육 기관: Kumar V

Oct 15, 2017

Good learning , teaches us how to diagnose and plan machone learning project.

교육 기관: Manage I O D S

Apr 23, 2020

As always loved the course, simulations were great and challenging to answer

교육 기관: Jeff N

Mar 18, 2018

I would have loved more programming assignments and opportunity to practice.

교육 기관: Animesh S

Jun 16, 2019

I see the point, but takes too long to make it. But part of a great series.

교육 기관: Umberto

Apr 05, 2019

useful hints and techniques to manage ML Projects and choose right approach

교육 기관: Sothiro P

Sep 11, 2018

I thought the course was clear and gave useful tips in leading a ML project

교육 기관: Vito D

Sep 22, 2017

A bit short, maybe combine this into other courses? Or expand it with labs?

교육 기관: Jean-Michel C

Dec 30, 2018

Very useful tricks / method to approach typical machine learning projects.

교육 기관: Mandlenkosi

Dec 10, 2018

I loved the use cases it gave a practical uses of what I've been learning.

교육 기관: subho c

Sep 30, 2018

Some hands on exercise to complement the theory would have been excellent.

교육 기관: Yisheng Y

Jan 25, 2018

I am pretty surprise that this course does not have programming assginment

교육 기관: dh

Oct 17, 2017

provide student with some code tests like previous courses may be better .

교육 기관: Ruifang W

Aug 23, 2017

quite detailed and easily accepted way of understanding all the materials.