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Вернуться к Structuring Machine Learning Projects

Отзывы учащихся о курсе Structuring Machine Learning Projects от партнера deeplearning.ai

4.8
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Оценки: 44,113
Рецензии: 4,968

О курсе

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....

Лучшие рецензии

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.

JB

Jul 02, 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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4326–4350 из 4,919 отзывов о курсе Structuring Machine Learning Projects

автор: Thomas P

Sep 21, 2017

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

автор: Nicolo d G

Feb 17, 2019

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

автор: Jose L M

Oct 02, 2018

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

автор: Sumesh R

Apr 09, 2018

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

автор: Victor P

Nov 10, 2017

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

автор: Francesco D Z

Sep 25, 2017

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

автор: Steve D

May 10, 2020

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

автор: Maik F

Apr 01, 2019

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

автор: José A M

Aug 05, 2018

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

автор: Kumar V

Oct 15, 2017

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

автор: Fredy A O L

May 29, 2020

El curso es muy bueno, le dá concenjos para emepzar a mirar redes neuronales

автор: Manage I O D S

Apr 23, 2020

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

автор: Jeff N

Mar 18, 2018

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

автор: Animesh S

Jun 16, 2019

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

автор: Umberto S

Apr 05, 2019

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

автор: Sothiro P

Sep 11, 2018

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

автор: Vito D

Sep 22, 2017

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

автор: Jean-Michel C

Dec 30, 2018

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

автор: Mandlenkosi

Dec 10, 2018

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

автор: subho c

Sep 30, 2018

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

автор: Yisheng Y

Jan 25, 2018

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

автор: dh

Oct 17, 2017

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

автор: Ruifang W

Aug 23, 2017

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

автор: Sergey I

Aug 22, 2018

Good and useful material. However the homework is not challenging enough.

автор: Nimrod P

Feb 06, 2018

Some video issues, give this course a slightly lower production values...