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Вернуться к AI Capstone Project with Deep Learning

Отзывы учащихся о курсе AI Capstone Project with Deep Learning от партнера IBM

4.5
звезд
Оценки: 352
Рецензии: 63

О курсе

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...

Лучшие рецензии

RK
30 июля 2020 г.

The capstone of the project was really good it helped me to understand the deep learning concepts clearly for providing the solution.

RB
22 мая 2020 г.

A very nice project based course to get hands on experience with deep learning\n\nand transfer learning.

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1–25 из 62 отзывов о курсе AI Capstone Project with Deep Learning

автор: Hernán C

2 апр. 2020 г.

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.

автор: Jeremiah J

24 февр. 2020 г.

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?

автор: Eric

29 янв. 2020 г.

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.

автор: Lam C V D

20 февр. 2020 г.

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

автор: Bhaskar N S

4 апр. 2020 г.

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.

автор: Denis U

11 мая 2020 г.

Is this really a professional certification ? Right now I don't think so. These tasks are for very very beginners. Not for professionals..

автор: Ravi P B

22 мая 2020 г.

A very nice project based course to get hands on experience with deep learning

and transfer learning.

автор: Sarath C G K

7 мая 2020 г.

The Course is good, The labs were crashing which were causing lot of issues in completing the course

автор: Yash R

28 мая 2020 г.

This is an excellent course if someone wants to learn transfer learning. However, having said that, there should be another task for which students should build their own model and compare its accuracy with the predefined one. With this, students would get insights as to how to build a deep learning model from scratch.

автор: Theodore G

28 янв. 2021 г.

Great course content! One thing that can be improved is the Skills Network portal. It's incredibly difficult to train any of the pre-trained models there.

автор: Vhui77@gmail.com

5 мар. 2021 г.

Not enough instructions as I wasted many hours without going to Google Colab. Please change it to AI review of project rather than peer review as most times there is insufficient submissions.

автор: Chaney O

8 июня 2020 г.

This course was incredibly frustrating. There were errors in the quiz questions out of one's control, which won't let one proceed without the correct answer to mis-written questions. It takes many days for instructor/and course assistants to respond to course forums. The IBM cognitive labs are too slow/not usable/crashes consistently and IBM Watson has severe credit limitations. Ultimately, searching the course forum threads from other students posts and running Google Colab on GPU were the only way I made it through. I definitely expected more from Coursera - more instructor interaction, working software and more TA visibility/guidance.

автор: Nopthakorn K

9 февр. 2020 г.

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

автор: Lee F

5 окт. 2020 г.

Course lecture are well done, but labs don't work properly. IBM should be able to do better. I am very familiar with Python and Jupyter notebooks. I have taken many courses with similar labs and have had almost no issues. I am disappointed, and will move on to AWS and Azure. When you move to the cloud, your stuff needs to work or people move on to the next service with a couple of clicks of a mouse. :-(

автор: A A A

8 июля 2020 г.

I got a chance to put what I learnt into practice and the idea of choosing between Keras Track or PyTorch Track was very beautiful. I can suggest another track for TensorFlow, making it a choice between choosing from 3 tracks instead. That would feel more complete.

автор: Mel A

19 июля 2020 г.

Although my laptop's GPU wasn't up to par, I managed to run the labs and finished the project with a lot of patience . Recommended course for AI enthusiast, data analyst and role as an engineer in data science.

автор: Ratheeshwaraa K

31 июля 2020 г.

The capstone of the project was really good it helped me to understand the deep learning concepts clearly for providing the solution.

автор: Harry

15 февр. 2021 г.

Learn a lot of interesting subject about calculate result with big data and deep learning. Thanks a lot

автор: Jacques J v R

6 янв. 2021 г.

This course was easy to follow and understand. It gives you all the tools to complete it with ease

автор: Alessandro F

5 апр. 2021 г.

A nice project to better understand the concepts learnt in the other courses of the program.

автор: Richard B

4 июня 2020 г.

Putting in practice what I learned and experienced positive results was very satisfactory.

автор: Suhas S

17 нояб. 2020 г.

AI Capstone project was really Interesting. I learned a lot during project. Thanks Team

автор: Siladittya M

24 июля 2020 г.

Very Good course. Learnt a lot from this course. Also got good hands-on experience.

автор: _Amir _

9 дек. 2020 г.

I'm very happy with that

i am proud of my self when i study in here

thanks a lot

автор: george s

1 окт. 2021 г.

Perfect project to apply everything learnt, just right difficulty.