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學生對 Coursera Project Network 提供的 Custom Prediction Routine on Google AI Platform 的評價和反饋

4.6
419 個評分
85 條評論

課程概述

Please note: You will need a Google Cloud Platform account to complete this course. Your GCP account will be charged as per your usage. Please make sure that you are able to access Google AI Platform within your GCP account. You should be familiar with python programming, and Google Cloud Platform before starting this hands on project. Please also ensure that you have access to the custom prediction routine feature in Google AI Platform. In this 2-hour long project-based course, you will learn how to deploy, and use a model on Google’s AI Platform. Normally, any model trained with the TensorFlow framework is quite easy to deploy, and you can simply upload a Saved Model on Google Storage, and create an AI Platform model with it. But, in practice, we may not always use TensorFlow. Fortunately, the AI Platform allows for custom prediction routines as well and that’s what we are going to focus on. Instead of converting a Keras model to a TensorFlow Saved Model, we will use the h5 file as is. Additionally, since we will be working with image data, we will use this opportunity to look at encoding and decoding of byte data into string for data transmission and then encoding of the received data in our custom prediction routine on the AI Platform before using it with our model. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

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PP

2020年4月24日

it was nice experience . the best thing you will learn that it is not much hard as wethink.

SS

2020年4月24日

Coursera has a great opportunity to utilise for every one in course ... thank you coursera

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51 - Custom Prediction Routine on Google AI Platform 的 75 個評論(共 83 個)

創建者 Yedke a A

2020年4月25日

Very nice

創建者 Anant N

2020年6月14日

Nothing

創建者 Meet V P

2020年5月17日

awesome

創建者 MAHALAKSHMI M

2020年4月25日

Do well

創建者 BATTU P T

2020年5月18日

Custom

創建者 k j

2020年7月2日

good

創建者 Pravendra S

2020年6月29日

nice

創建者 p s

2020年6月24日

Good

創建者 Vajinepalli s s

2020年6月17日

NICE

創建者 Chandra k K

2020年6月8日

good

創建者 AISHWARYA V

2020年6月4日

good

創建者 Sai K R K

2020年5月26日

good

創建者 MADIREDDY L M

2020年5月23日

Nice

創建者 PONDARA K

2020年6月1日

5

創建者 MANIKANTA S

2020年5月26日

5

創建者 An T

2020年5月14日

Very good introductory course on how to deploy a model on GCP. However, the project was a bit short in my opinion. Some steps are not explained thoroughly on why we do things in certain ways. But overall, this project gave me a really good learning experience and exposure to GCP.

創建者 srinivas d

2020年6月5日

It would be good if it allows to ask questions, I got the response as invaid due to some unknown issue, how to resolve this error, why i got this error? It is good if you explains you might get these type of errors and how to resolve those errors also included.

創建者 Aditya P

2020年6月1日

thank you for giving some basic knowledge in google AI but i requst you guys to do this with online live classes so that from different field persons like mechanical , civil will also learn nd get it clearly thank you .! but it was so good

創建者 Jojo W

2020年5月26日

The VDO files are not like what I see on the current GCP. It's quite hard to follow the instructor.

創建者 Li-Ting T

2020年7月13日

Just walkthrough online documents

創建者 NIRNIMESH D

2020年6月2日

very helpful and interesting

創建者 Mohit K 1

2020年5月31日

Its a nice project course

創建者 sagar s

2020年5月20日

it was pretty good....

創建者 Sapna D

2020年7月13日

That's fine

創建者 Pawan K

2020年5月8日

Awesome...