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AI Capstone Project with Deep Learning に戻る

IBM による AI Capstone Project with Deep Learning の受講者のレビューおよびフィードバック

4.3
88件の評価
17件のレビュー

コースについて

In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use a library of their choice to develop and test a deep learning model. They will load and pre-process data for a real problem, build the model and validate it. Learners will then present a project report to demonstrate the validity of their model and their proficiency in the field of Deep Learning. Learning Outcomes: • determine what kind of deep learning method to use in which situation • know how to build a deep learning model to solve a real problem • master the process of creating a deep learning pipeline • apply knowledge of deep learning to improve models using real data • demonstrate ability to present and communicate outcomes of deep learning projects...

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AI Capstone Project with Deep Learning : 1 - 17 / 17 レビュー

by Eric

Jan 29, 2020

Course opened late. One instructor did not prepare his materials and the exercises were not even accessible. I will not be purchasing from Coursera in the future because of this specialization course. Truly a huge waste of money.

by Lam C V D

Feb 20, 2020

But need to study extra as these topics are not taught like Transfer Learning

by Jeremiah J

Feb 24, 2020

I guess the course was OK, but the complete limitations of the "provided" compiling environment is inexcusable. I tried five different emulators, eventually using Google's Colab tool in order to get any type of results within six hours. I don't know what you can do, but something needs to be done.

Also, I would recommend NOT having two different tracks (Keras & Pytorch). Because of the aforementioned coding issues, most of the real instruction occurs in the discussion forum. It is INCREDIBLY confusing when there are essentially two different assignments posting questions in the same space. Also, can you do something about all my "classmates" asking for people to review their work in the forum? In my opinion, that is NOT the purpose of the discussion forum. As the admins, can you please just delete those requests to make it easier to find the REAL discussions. You are smart computer scientists, can't you create an AI to filter all those posts into the bit-bucket?

by sanchit k

Apr 04, 2020

Please labs are not so good. Please improve it.

by Christos

Feb 25, 2020

Challenging!!

by Carlos F C d S e S

Mar 26, 2020

Thank you!

by Alvaro A B A

Apr 06, 2020

Excelent

by Thar H S

Mar 27, 2020

Thank a lot for creating this course. It really useful and practical for me.

by Hernán C

Apr 02, 2020

Its takes to long to train the models (6 hours each case). I was lucky because some students give me de advice to use google Free GPU to complete the each train in 2 minutes. Without the students tips It is impossible.

I suggest to add to this course information about to use either cuda with own local jupyter lab or either recommend some serice like googel colab to get better performance.

by charles l

Feb 24, 2020

This course was riddled with operational flaws regarding the image data, and how it operated in the IBM framework. At one point I was not able to run the labs with either PyTorch or Keras versions, and eventually just downloaded the notebooks and ran them in Google Colab to complete the specialization.

by Bhaskar N S

Apr 04, 2020

Most of this course is lab-work. However, the lab environment was inadequate. It kept crashing, disconnecting, or went to slow. While I understand that the Lab is a 3rd party tool, my payment was made to Coursera, hence they need to help ... at least by extending access for the lost time.

by Yinias

Feb 06, 2020

The data from the course is not well prepared, some invalid pictures in the data. And also sometimes the IBM platform can not run the training well, loss connection and need several hours of time for training the model...

by Alexis b

Mar 24, 2020

This is a good enough project if it is your first Pytorch implementation. However, the program is unevenly difficult, with very few information for week3 assignment, and almost copy/paste assignment for week4.

by Reinaldo L N

Feb 04, 2020

The docker environment by IBM is horrible. I just got to finish my course running all the notebooks locally (except for those at the Watson environment)

by Lee Y Y

Feb 09, 2020

Not well-prepared materials in Keras, especially in Week 3 (model-training) which took more than 3 hours to training and even not successfully.

by Nopthakorn K

Feb 10, 2020

Capstone project had delayed for a month, and after that the course resource also not ready.

by Mriam A

Apr 03, 2020

the keras part was totally ignored