Видео

Thanks Mike, this is cool stuff. An cdk version of this would be awesome.

This is great knowledge Mike, can I trouble to get GitHub link want to play around to build a CI/CD pipeline for deploying Generative AI applications through code

Found your channel from LinkedIn, great stuff!

great content! Thanks for sharing.

Hi Mike, The way explanation is very good. I want to know about AWS machine learning certification -associates course.

The future is here 😮

Good stuff 👍

Would love to see something on how we could use sagemaker containers in a real word use case

Yesterday I wrote a science fiction story in my mother tongue Malayalam, with MENACE being the main motif. 🙂

Thanks Mike. Finding myself (as an SA) having to learn a lot about SageMaker in very little time, and this was super helpful.

looking forward to trying this!

Hi Mike great presentation. Do you know if Sagemaker supports S3-compatible data source for data ingestion?

Thank you for the great explanation and effort. I still have trouble understand the pros of having IDE's in aws, such as notebooks, studio, cloud9 and so on. Why would I pay for computing, when I can simply use my favorite IDE's on my own computer? One argument is that IDE in the cloud gives full integration to AWS services, But on my own computer, I can log in via cli with sso, and use the sdks.

great content

I think I'm not the only one who chose AWS instead of Azure just because of Mike.

thank you for the demo and explanation. worth of my time in less than 20 minutes to have a nutshell of AWS Rekognition!

@mikegchambers great video - just wondering if there would be any additional adaptations to make if you were training a deep learning model with eg. pytorch/fastai?

Thanks Mike. It was great intro to AWS StageMaker.

Please share code for the above project. Looks very interesting.

You could spend weeks (months) going down the infinite rabbit hole (hell hole) that is AWS official documentation and not come away with anything like the clarity that this video gives. Similarly, this is orders of magnitude better than the vast morass of badly presented, desperately confusing, inaudible yawnfest YT videos on Sagemaker. Superb content. Please make more!

Thank, this video is quite good for understanding how to manage costs in aws

Great video and explanation than any other AWS Rekognition videos out there. One question, the command line response was just the label and the confidence score. How did you pull up the correct image out of the returned custom labels? what if multiple custom labels are returned? I have a similar use case and this would be greatly useful

10 seconds into the video, and this is SO much better then a little webcam and poop audio. Thanks for being so engaging.

Am begginer to the AWS Sagemaker with the requirement for our client project and you have explianed the difference between studio and notebook in extrodinary way. Anyone can understand it easily without any background knowledge. Thank you

Great video Mike - I am new to Sagemaker but you have broken it down in to manageable understandable pieces

Great video. Feel like I got a clear understanding of the various tools there. Looking forward to your video on sagemaker studio vs sagemaker studio lab ;)

Banging video @mikegchambers. I owe you a drink when you're next in Cardiff :)

Why can't AWS make such useful videos?

Are you available to share your AWS account with me? I pay

Do I need to buy sagemaker book? I already have AWS basics, Azure basics and AWS architect books. Companies called me for interview and rejected me. Refund the money I spent on Mobiles and tickets.

really needed to understand the pricing and free tiers verbally. Thank you so much!

感谢您的分享，您的讲解非常的清晰且具有系统性和大局观。我会继续浏览您的其他视频，期待找到适合我学习SageMaker的其他内容。

Like best video ever?

what is the difference between Sage Maker Canvas and Sage Maker Studio ?

🔝☁‼

holy %$%^ this was super amazing man

Excelent video! Thanks for the time and effort

Great job in making this demo so engaging!

In Canvas, is there a python script for training the data (includes the algorithm used to train the data) gets created that I can download, other than the model notebook ?

Is this endpoint needs an API gateway, and maybe lambda, so I can inference from outside AWS world ?

great video, SM_MODEL_DIR, SM_CHANNEL_TRAIN, SM_CHANNEL_TEST, these have default /opt/ml locations defined in sagemaker python sdk? And once we pass the s3 bucket location, the data from the s3 bucket is automatically pulled into the sagemaker training job containers?

Great demonstration!

great simple explanation...Thank YOU.

Hi Mike, you are a gifted teacher. I frequently watch a lot of videos, but your explanation and to the point no one can beat it, trust me 😊thank you again for the video

Thank you very much this is really awesome

I like how you mentioned to use it for sharing with future self...this is the main reason I'm looking into starting out with Jupyter as I've some old py scripts with great data cleansing tasks I've almost forgot why I did a certain thing lacking the comments etc. looking forward to experimenting with this and onboarding to utilise Jupyters functionally. Thanks for the short video 👍

Thank you Mike! Very helpful. You have explained it very well. Loved it.

Great job, Mike, good explanation.

great video! you are very clear in the knowledge, just enough visualisation to bring the point across. and I love how you start from the big picture and zoom in, rather than people who go at the individual cog of the system to try to explain it all one by one..

Nice video Mike