How To Deploy ML Models With Google Cloud Run
ฝัง
- เผยแพร่เมื่อ 21 ก.ค. 2024
- Learn how to deploy Machine Learning / Deep Learning models with Google Cloud Run. We build a simple app with TensorFlow and Flask, containerize it with Docker, and deploy it to Google Cloud Run.
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#Python
Resources:
cloud.google.com/sdk/docs/ins...
cloud.google.com/run/docs/qui...
sararobinson.dev/2020/08/18/m...
TensorFlow course: • TensorFlow 2 Beginner ...
PyTorch course: • PyTorch Tutorials - Co...
Timeline:
00:00 Introduction
00:52 Prepare Model
04:27 Write Flask App
12:20 Setup Google Cloud Project
12:59 Google Cloud SDK
13:47 Dockerfile
16:41 Deploy
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What other deployment methods would you like to see?
Is Google cloud service free to train model?
AWS would be amazing
Aws, Azure, docker, etc
@@anelm.5127 thanks, yes will definitely do AWS
@@sakilahmed6788 There is a free tier which is enough to play around with it
Thank you very much sir. Your tutorial really helped me. I'm so glad I finally found a tutorial that worked for me 😁
Great job as always man 👏 much appreciated, alot of people show how to create a ml app but not how to deploy it
glad you like it!
This was extremely helpful. Thank you so much!
Thank you for your great videos, I have been using python for past 3 years but still didn't know many things, or using those things with knowing. I hope other would take advantage of these excellent tutorials, I will surely encourage my friends to watch and subscribe.
thanks! I also still don't know many things ;) you should never stop learning...
Wow man I am glad I subscribed I was there when you just started and so much proper content since then it’s amazing! Thank you so much for all this!!!!! Great stuff !!!!
Happy to hear that :) Thanks so much for your support!
@@patloeber Would it be possible to do one with app engine?
Hello!
Thanks for this great tutorial. I have one question. We need to install docker in our computer to deploy the model on gcp?
It works for the first time but throws error on 2nd deploy:
Revision 'getprediction-00002-ved' is not ready and cannot serve traffic. The user-provided container
failed to start and listen on the port defined provided by the PORT=8080 environment variable.
Thanks for a great video. In addition to the video content, can you build a simple webapp using Dash and show the demonstration? Preferably, the end user can upload the image in the webapp and see the classification result. That will be cool!
thanks bro, you helped me a lot
Any way to use GPU for the heavy computation model?
great demo!
here you only had one "method" - index, what if i have multiple? do i have to do gcloud build multiple times?
how i can fix this error
The user-provided container failed to start and listen on the port defined provided by the PORT=8080 environment variable. Logs for this revision might contain more information.
Awesome thank you.
How can I do if I want an esp32-cam to send the video live to the model deployed in Google Cloud?
I run a FastAPI ML for an android app. I did your process but it runs into an error said "Internal Server Error", what's the problem with this?
@patloeber Hi , I am getting CORS error after deploying a Sequential model using Keras, ML model when i am using it in my react app . Can you please help me. In Model I have different layers like embeding layer, Lstm layer etc.
Nice tutorial, thank you!
Glad it was helpful!
I want to deploy a small application for Machine Learning. It is using BigQuery. Volume of data is medium high.
I want a CICD pipeline.
The application is only for business users. What service should I use for deployment on google cloud ?
How code request from android studio to get prediction?
Is it posible to use fastapi on google cloud run?
Just finished learning ML and was looking how to deploy. Awesome
where did you learn?
You're never done with learning ML ;) But congrats! Hope you'll enjoy the video
@@patloeber true. The basics i guess. Thanks for the tutorial. Really appreciate.
@@gilbertlopez udemy data science course by Jose Portilla. the good thing about this course is it covers the basic maths theory, example and then exercise.
@@jaggyjut awesome thanks for the recommendation!
gracias por todo el conocimiento dado.
Can`t wait for this! Also will you do kubernetes in future some time too ?
Great suggestion! I will have to look into this...
another great topic!
thanks!
Your video Literally saved my ass ...Dankeschon
Does Cloud Run support GPU now?
love you! can we deploy tf2 models without docker and just using app engine
Best 👍👍👍 one
Awesome
Could you tell me font or thema using in your pycharm? look so good!
It's the Dracula Theme
import requests
resp = requests.post("127.0.0.1:5000/", files={'file': open('three.png', 'rb')})
print(resp.json())
Output:
Traceback (most recent call last):
File "d:\Self Learning- Tutorial\Python-PE Advance PYthon\GoogleCloudML_Deployment\test\test.py", line 3, in
resp = requests.post("127.0.0.1:5000/", files={'file': open('three.png', 'rb')})
FileNotFoundError: [Errno 2] No such file or directory: 'three.png'
I did have three.png, why is it not running the prediction function here? I stopped main.py and run test.py.
Do I have to run the main.py at the same time? btw I am using VS code.
Exciting stuff but this requires billing to be enabled right?
Yes I think you need to enable it, but there is a free tier to play around with it
Special thank for making tutorial on Deploy ML Models With Google Cloud Run. However, could you/everyone assist me on the next step that I want to implement "test.py" in HTML. I mean that I want to run resquests.post with my serviceURL from GCP in another index.html. Hope to receive help from everyone. Thank you so much in advance.
we have to enable billing for this yes or no Bro
Yes I think you need to enable it, but there is a free tier to play around with it
Anyone face this issue? Gcloud is not recognised as an internal or external command
What Tensorflow version are you using?
2.x in this video...
@@patloeber Cool =)
Perfect example man, but is possible use GPU with GCP cloud run ?
yes it's possible, but not for free of course
@@patloeber There is no direct support for GPUs with Cloud run. You can do it with Cloud Run for Anthos, but for that, you again need a Kubernetes Cluster somewhere.
Did anybody else get this error?
ERROR: (gcloud.run.deploy) Cloud Run error: Container failed to start. Failed to start and then listen on the port defined by the PORT environment variable. Logs for this revision might contain more information.
yes, first run it worked but 2nd deploy I saw the error, any clue how to fix it?
Great
thanks :)
In pycharm
You will useing Linux
total fraud, your thumbnail said app deployement.