HIRING: Data Engineer - HSS Orthopedic Data Innovation Lab / New York, NY, United States 👉 https://ai-jobs.net/J63212/ #AI #MachineLearning #DataJobs #Jobsearch #MLjobs #bigdata #DataScience #AIjobs #techjobs #hiringnow #job #FHIR #spark #ETLjobs #SQLjobs #SageMaker #Research

🧐 Andy Jassy, ​​CEO di #Amazon, scopre le carte sull'#AI generativa durante la condivisione dei dati del Q2. 
💡 Com'era prevedibile, racconta una visione orientata alle applicazioni consumer, ma soprattutto all'integrazione dei modelli nei flussi delle aziende, che possono contare su un ecosistema #AWS ancora più completo.

#IntelligenzaArtificiale #LLM #Bedrock #SageMaker #GenerativeAI

https://www.linkedin.com/posts/alessiopomaro_amazon-ai-aws-activity-7093477372892463105-Lbo3

New Amazon QuickSight capabilities:
• Programmatically export Paginated PDF Reports and CSV content with Snapshot Export APIs https://aws.amazon.com/about-aws/whats-new/2023/07/amazon-quicksight-snapshot-export-apis/
• Analysis menu for enhanced navigation and efficiency across Analysis Experience https://aws.amazon.com/about-aws/whats-new/2023/07/amazon-quicksight-analysis-file-menu/
• Using SageMaker Canvas ML model predictions in QuickSight analyses https://aws.amazon.com/about-aws/whats-new/2023/07/amazon-sagemaker-canvas-sharing-ml-models-amazon-quicksight/
#AWS #QuickSight #SageMaker

Llama 2 foundation models from Meta available in Amazon SageMaker JumpStart
https://aws.amazon.com/about-aws/whats-new/2023/07/llama-2-foundation-models-meta-amazon-sagemaker-jumpstart/
SageMaker JumpStart, a ML hub that offers pretrained models, built-in algorithms, and pre-built solutions. You can deploy and use Llama 2 foundation models with a few clicks in SageMaker Studio or programmatically through the SageMaker Python SDK.

Llama 2 is an auto-regressive language model that uses an optimized transformer architecture https://ai.meta.com/llama/

#AWS #SageMaker #ML #AI #Llama

生成AI使ってサカバンバスピスを鮮魚コーナーに並べてみた
https://qiita.com/minorun365/items/3b91dcb6a3bca81fa388?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items
#AWS #SageMaker #StableDiffusion #生成AI #サカバンバスピス

AWS's #Sagemaker offering feels like a Fata Morgana of convenience and ease-of-use, but when you take some steps towards the oasis it vanishes and a booming voice sounds "YOU FOOL, you should have learned Docker, ECS, CloudFormation, CodeBuild, ..."

The more I dig in with the Hugging Face the more I fall in love. I felt this with AWS before, now this is the new toy for me. Having to implement non-transformer models to load with them and train them is a fully new subject that I can get in with.
#huggingface #sagemaker #AWS

Updated AWS::SageMaker::InferenceExperiment

Use the AWS::SageMaker::InferenceExperiment resource to create a new inference experiment for comparing model variants on a SageMaker endpoint.
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-inferenceexperiment.html #sagemaker #cloudformation

I love my code:
- translated from local #RStats to #sagemaker #python
- connects to #AWS 's RDS and S3
- makes #API calls
- uses #geojson and intersection

(still, for handling dataframes, R is better IMO)

I'm impressed
5seconds in #sagemaker vs 30 seconds in local
The most challenging task has been translating my code from #rstats to #Python
(Still, I prefer R)

I used wordcloud to count words used in appraisals of properties
In #RStats , and also a version in #Python using #sagemaker .

Wrote about it, in spanish,
https://medium.com/@mikael_mm/cu%C3%A1les-son-los-t%C3%A9rminos-m%C3%A1s-frecuentes-utilizados-en-una-valuaci%C3%B3n-78dfe8d13dc2

My code in Sagemaker ran in 30secs, while the "same" code took 90secs.

The code involves reading individual files located in S3, and gathering specific lines.

#rstats #Python #sagemaker

just finished my first python notebook in Sagemaker using xgboost with data storaged in my own RDS. #AWS #sagemaker #xgboost

RT @ClarityAIEng
Is your Team Starting to use #SageMaker ? Do you want to power up? Our Lead Lead Data Scientist Robert Smith shares his experience with @awscloud 🚀SageMaker Studio for Team Collaboration🚀 in this 🟩Medium Post🟩

https://medium.com/clarityai-engineering/sagemaker-studio-for-team-collaboration-98acc886ff54

Updated AWS::SageMaker::ModelCard

Use the AWS::SageMaker::ModelCard resource to create an Amazon SageMaker Model Card.
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelcard.html #sagemaker #cloudformation

HIRING: MLOps Engineer / Mexico - Remote https://ai-jobs.net/J41149/ #AI #MachineLearning #DataJobs #AIcareers #MLjobs #bigdata #DataScience #AIjobs #hiringnow #RemoteJob #AWS #Docker #MachineLearning #MLOps #PyTorch #SageMaker #Scikitlearn #TensorFlow

Updated AWS::SageMaker::Space

Use the AWS::SageMaker::Space resource to create a new shared space for use in a Domain.
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-space.html #sagemaker #cloudformation

Updated AWS::SageMaker::ModelCard

Use the AWS::SageMaker::ModelCard resource to create an .
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelcard.html #sagemaker #cloudformation

Ok, is there a Chrome extension or something that makes #Amazon #AWS services not look like absolute utter shit? All this empty space and #SageMaker decided to put a single notebook instance on page 2.

Updated AWS::SageMaker::FeatureGroup

Use the AWS::SageMaker::FeatureGroup resource to create a new feature group using either an Apache Iceberg or Glue table format.
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-featuregroup.html #sagemaker #cloudformation