Build train and deploy model in sagemaker | sagemaker tutorial | sagemaker pipeline

Build train and deploy model in sagemaker | sagemaker tutorial | sagemaker pipeline
#sagemaker #aws #datascience #machinelearning
Hello,
My name is Aman and I am a Data Scientist.
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About this video:
Build train and deploy model in sagemaker
sagemaker tutorial
sagemaker pipeline
sagemaker studio tutorials
sagemaker endpoints
sagemaker studio lab
About Unfold Data science: This channel is to help people understand the basics of data science through simple examples in an easy way. Anybody without prior knowledge of computer programming or statistics or machine learning and artificial intelligence can get an understanding of data science at a high level through this channel. The videos uploaded will not be very technical in nature and hence can be easily grasped by viewers from different backgrounds as well.
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The Art of Data Science By Roger D. Peng - amzn.to/2KD75aD
Predictive Analytics By By Eric Siegel - amzn.to/3nsQftV
Data Science for Business By Foster Provost - amzn.to/3ajN8QZ
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Naked Statistics By Charles Wheelan - amzn.to/3gXLdmp
Practical Statistics for Data Scientist By Peter Bruce - amzn.to/37wL9Y5
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Introduction to machine learning by Andreas C Muller - amzn.to/3oZ3X7T
The Hundred Page Machine Learning Book by Andriy Burkov - amzn.to/3pdqCxJ
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[@contactdi8426]

Bro... listen!! This is the FIRST video I just watched yours and I have genuinely became your FAN..What a exceptional explanation for each and everything.. you just knew what to skip and what to explain by comparing everything in local vs cloud scenarios. Thanks a lot

[@UnfoldDataScience]

Thanks a lot. Welcome to unfold data science family.

[@gouthamkarakavalasa4267]

Sir, a Humble request form my side.., I can see the number of likes are way to lees than they are supposed to be. But I request to please continue uploading the video's, as few of are great fans of you. we trust your content, and when I search any deep learning topic, if I see your playlist, I will directly open your videos. Please keep uploading for people like us.

[@UnfoldDataScience]

Your comment is precious to me

[@kdfox2007]

As a complete idiot when it comes to neural networks, this video is a fantastic introduction. Thank you.

[@UnfoldDataScience]

Thanks for watching.

[@sriramdesetti5979]

Exactly looking for the same, every other creator is explaining the same architecture diagrams which are their in official aws docs/channel. Nice work Bro 😀

[@bernhardvoggenberger9850]

yes, I came to understand what transferring normal code to aws would look like, and you told me exactly that! Thank you!

[@UnfoldDataScience]

Glad I could help!

[@doaaaboomar-d6e]

Hello sir, thanks for this great explanation , I just want to inform you that the practice link provided in the description is for creating a notebook not using sagemaker studio like you do Thank you very much, keep it up

[@ssss-u7w]

very good, how to deploy a custom model from tar gz file ? plz make video on that

[@liyatle]

I love you

[@skyforever1000]

good and easy tutorial, way more better than the aws official one

[@manjunathabr156]

Great Videos in the playlist sir, but was disappointed to see you skipped the module on how the basic build train and deployment work and said you guys already know. I wish you had a video on that as well.

[@princekhunt1]

Great Great Great

[@parultaneja9276]

Thanks Aman to share the knowledge, I want to know is there any other way for the real-time prediction of the data through ML model specifically for IoT device.

[@princekhunt1]

Question: does amazon count bill on running the commands (where excetly we do use cloud) or per hour (time based)?

[@UnfoldDataScience]

Not on commands, billed on capacity used

[@aakashsharma1126]

Great explain , need more video on sagemaker

[@antonmladenov8781]

great stuff, broski! keep those SageMaker videos coming! 💪💪💪💪💪

[@UnfoldDataScience]

Thanks Anton. Your comment is precious to me.

[@rameshrudra2387]

Thanks bro for this video

[@ShivarajKarki]

Thank you

[@kdfox2007]

Thanks!

[@ryanprasad2090]

Badass explanation. Thanks!

[@UnfoldDataScience]

Thank you. Pls share with friends

[@explorewithskp1237]

Sir how to call the data from local machine or from other databases and is this the same way that we do in real time ?

[@explorewithskp1237]

Sir kindly reply with a solution not with a love symbol pls

[@jawadasif8130]

great explanation

[@BibekGhorasainee]

what is the cost of deploying a model in amazon sagemaker?

[@nkorochinaechetam2516]

nice one man

[@pouriaforouzesh5349]

🙏

[@sudhirkumarshahu6146]

Bhai Ipynb file ka link deta ya git pe daal deta to kya bura ho jata.

[@deepaktripathi4094]

Hello Sir, You have deleted the end point here just because you were giving tutorial. On production environment, we never delete endpoint right? Please correct me if i am wrong.

[@UnfoldDataScience]

Yes to save cost I deleted

[@umeshtiwari800]

Excelent

[@UnfoldDataScience]

Thanks Umesh. long time..hope you are doing good

[@mainuddinali9561]

plz provide full script also from initial

[@belxismarquez4447]

github?

[@ShubhamKumar-xy6kj]

Please provide the code script for reproducibility

[@thamizhansudip6644]

Fantastic job 👏👏

[@MrMela69]

great video. The downside is there is no code. Would be nice if you provide a link to the code in the description for each video. Stopped watching because unable to reproduce the result with out code.

[@UnfoldDataScience]

Thanks for feedback, keep watching. I will try to add it in git. github.com/UnfoldDataScience

[@sudhirkumarshahu6146]

@@UnfoldDataScience I guess you didn't added that.