You typically don't want to expose Sagemaker endpoint to the public. I'm guessing he's trying to mimic real world where you are integrating with an application. Using apigateway allows you to customize a different payload as well.
Thank you for making this video. I am trying to follow along this video. Now the Jupyter notebook code of Breast cancer dataset is not available. Could you please advise where can we find the same code?
Thanks a lot my bro! Do you know what's the average cost of mantaining this structure 24h/30 days per month inservice? Cause I have a simple logistic Regression model that i would like to serve to an external javascript front end
Thank you again for watching this tutorial, I really hope it was useful and worth your time. In addition to that, if your really like AWS for ML and DevOps, I created (and still creating) a special RUclips channel for this, check it out here: ruclips.net/p/PLjJWtyuv5yrrMl5xVF5B_NrMcb7fjenDt The best place to learn Data Science with the best in the industry - Turing College. READ MORE HERE: turingcollege.org/DataScienceGarage - Suggest the topic for the next video! - Share you experience on this tutorial below! Appreciate it!
The video is awesome! It's very comprehensive and useful! I have a question about the API Gateway. If we want to access the model endpoint from other AWS services like EC2, do we still have to use lambda and API Gateway? It seems like combining lambda and API gateway is for the external user. Thanks a lot!
Where can I get the notebook and code? So the process to generate predictions is to invoke an already created endpoint and then run predictions on top of it?
HI, thanks for your content!!!! I have one question. I have large NLP model and it requires GPU. If so does lambda use computing resources? or sagemaker?
this is a very high quality channel, thank you
Thank you for watching! You are welcome :)
that step by step , 3 step explanation was a real eye opener was able to understand the big picture
Short and clear video to understand easily. Thanks
Thanks for watching, appreciate! :)
Thank you so much man, this is some top notch quality content !
What an amazing video. I can't say enough thanks
Big pleasure to see such feedback, appreciate!
This was very helpful. Thank you!
Hello. The Sagemaker endpoint can take requests and scale up if needed. Why do we need another wrapper as lambda on it?
You typically don't want to expose Sagemaker endpoint to the public. I'm guessing he's trying to mimic real world where you are integrating with an application. Using apigateway allows you to customize a different payload as well.
clearly explained for beginner. thank you
Thank you for watching! Appreciate your feedback! :)
Superb explanation!
Thanks for such feedback! Appreciate! :)
Thank you for making this video. I am trying to follow along this video. Now the Jupyter notebook code of Breast cancer dataset is not available. Could you please advise where can we find the same code?
the Best ML Sagemaker video. Thank you for sharing!
Thanks for watching! That's inspiring to create more :)
Thanks a lot my bro! Do you know what's the average cost of mantaining this structure 24h/30 days per month inservice? Cause I have a simple logistic Regression model that i would like to serve to an external javascript front end
labai gerai paaiskinta. Achiu
Ačiū, kad žiūrite! :)
Thank you again for watching this tutorial, I really hope it was useful and worth your time.
In addition to that, if your really like AWS for ML and DevOps, I created (and still creating) a special RUclips channel for this, check it out here: ruclips.net/p/PLjJWtyuv5yrrMl5xVF5B_NrMcb7fjenDt
The best place to learn Data Science with the best in the industry - Turing College.
READ MORE HERE: turingcollege.org/DataScienceGarage
- Suggest the topic for the next video!
- Share you experience on this tutorial below! Appreciate it!
Amazing! I am still figuring out how to automate process of running my model to score every two weeks.
@@nishantkumar-lw6ce Thanks for feedback, appreciate!
@@DataScienceGarage Can you help share ideas on how I can setup an automated code run based on batch inference from trained model?
Useful one! Thanks for sharing!
The video is awesome! It's very comprehensive and useful! I have a question about the API Gateway. If we want to access the model endpoint from other AWS services like EC2, do we still have to use lambda and API Gateway? It seems like combining lambda and API gateway is for the external user. Thanks a lot!
Where can I get the notebook and code? So the process to generate predictions is to invoke an already created endpoint and then run predictions on top of it?
HI, thanks for your content!!!!
I have one question.
I have large NLP model and it requires GPU.
If so does lambda use computing resources? or sagemaker?
End to end explanation .Thanks for this video.
Thanks for watching! Appreciate your time!
Beautiful 😍
thanks a lot
Super educational video, very clear to understand.
Thx Amigo!! gl hf
This video needs more visibility !!
Thanks! Share, like and subscribe! :))
in this everything comes in free tier or will they charge?
Subscribed ! Thank you for the tutorial. It will be good if you can let us know how we can use AWS Model Registry adding to this architecture.
good
Thanks!
so how do i connect a web app ui so that a client can visit a public ip address and make request from a public address from aws
Hi can you show similar thing in R too, it would be very helpful
Sorry, I have almost zero experience in R...
Can we have notebook for demo practice from github or gitlabs
how much does it cost to try it?
Anyone knows how can I invoke predictions with JavaScript?
...is he trying to fake indian accent? Honest q. great content.