What we're about

This meetup is focused on Data Science on AWS as well as open source AI/ML technologies.

Upcoming events (5)

Workshop: Build an AI/ML pipeline with BERT, TensorFlow and Amazon SageMaker

Online Workshop - See Details Below

Workshop: Build an AI/ML pipeline with BERT, TensorFlow and Amazon SageMaker

RSVP: https://www.eventbrite.com/e/full-day-workshop-kubeflow-bert-gpu-tensorflow-keras-sagemaker-tickets-63362929227

**Description**

In this hands-on workshop, we will build an end-to-end AI/ML pipeline for natural language processing with Amazon SageMaker.

You will learn how to:

• Ingest data into S3 using Amazon Athena and the Parquet data format
• Visualize data with pandas, matplotlib in Jupyter notebooks
• Run data bias analysis with SageMaker Clarify
• Perform feature engineering on a raw dataset using Scikit-Learn and SageMaker Processing Jobs
• Store and share features using SageMaker Feature Store
• Train and evaluate a custom BERT model using TensorFlow, Keras, and SageMaker Training Jobs
• Evaluate the model using SageMaker Processing Jobs
• Track model artifacts using Amazon SageMaker ML Lineage Tracking
• Run model bias and explainability analysis with SageMaker Clarify
• Register and version models using SageMaker Model Registry
• Deploy a model to a REST Inference Endpoint using SageMaker Endpoints
• Automate ML workflow steps by building end-to-end model pipelines using SageMaker Pipelines

**Pre-requisites**
Modern browser - and that's it!
Every attendee will receive a cloud instance
Nothing will be installed on your local laptop
Everything can be downloaded at the end of the workshop

**Location**
Online

Related Links
=============
O'Reilly Book: https://www.amazon.com/dp/1492079391/
Website: https://datascienceonaws.com
Meetup: https://meetup.datascienceonaws.com
GitHub Repo: https://github.com/data-science-on-aws/
YouTube: https://youtube.datascienceonaws.com
Slideshare: https://slideshare.datascienceonaws.com
Support: https://support.pipeline.ai

Data Science on AWS Monthly Webinar: Advanced Analytics and AI/ML

Online Workshop - See Details Below

RSVP Webinar: https://www.eventbrite.com/e/1-hr-free-workshop-pipelineai-gpu-tpu-spark-ml-tensorflow-ai-kubernetes-kafka-scikit-tickets-45852865154

Zoom link: https://us02web.zoom.us/j/82308186562

Talk #1: Distributed GPU Training using Hugging Face Transformers and Amazon SageMaker by Philipp Schmid, ML Engineer @ HuggingFace 🤗

I will start with a introduction of Hugging Face as company, what we do and offer. I'll then talk a bit about our Partnership with AWS and how practitioners can run distributed training for model/data-parallelism on Amazon SageMaker using both HuggingFace Transformers and Amazon SageMaker distributed libraries. I will provide a comprehensive tutorial including notebooks and source code.

Title: Start Your ML Journey Quickly with SageMaker JumpStart by Dr. Li Zhang, Principal Product Manager for SageMaker Jumpstart @ AWS

I will introduce SageMaker JumpStart, a newly launched feature of SageMaker providing you a quick way to get started with solving your machine learning problems.

SageMaker JumpStart provides 184 popular vision and text models from popular model zoos, 16 pre-built, end-to-end solutions that solve common business use cases, notebooks, blogs, and video tutorials designed to help you learn and remove roadblocks. SageMaker JumpStart makes it extremely easy for experienced practitioners and beginners alike to quickly deploy and evaluate models and solutions, saving days or even weeks of work.

By drastically shortening the path from experimentation to production, SageMaker JumpStart accelerates ML-powered innovation, particularly for organizations and teams that are early on their ML journey, and haven’t yet accumulated a lot of skills and experience.

Bio:
Dr. Li Zhang is a principal product manager technical for SageMaker JumpStart, Amazon SageMaker built-in algorithms that help data scientists and machine learning practitioners get started with training and deploying their models, and for the use of reinforcement learning (RL) with Amazon SageMaker.

Talk #3: Apache Spark on SageMaker by Chris Fregly, Principal Developer Advocate @ AWS

I will discuss various ways to use Apache Spark on SageMaker including data transformations and machine-learning-based product recommendations.

RSVP Webinar: https://www.eventbrite.com/e/1-hr-free-workshop-pipelineai-gpu-tpu-spark-ml-tensorflow-ai-kubernetes-kafka-scikit-tickets-45852865154

Zoom link: https://us02web.zoom.us/j/82308186562

Meetup: https://meetup.datascienceonaws.com

Related Links
=============
O'Reilly Book: https://www.amazon.com/dp/1492079391/
Website: https://datascienceonaws.com
Meetup: https://meetup.datascienceonaws.com
GitHub Repo: https://github.com/data-science-on-aws/
YouTube: https://youtube.datascienceonaws.com
Slideshare: https://slideshare.datascienceonaws.com
Support: https://support.pipeline.ai

Workshop: Build an AI/ML pipeline with BERT, TensorFlow and Amazon SageMaker

Online Workshop - See Details Below

Workshop: Build an AI/ML pipeline with BERT, TensorFlow and Amazon SageMaker

RSVP: https://www.eventbrite.com/e/full-day-workshop-kubeflow-bert-gpu-tensorflow-keras-sagemaker-tickets-63362929227

**Description**

In this hands-on workshop, we will build an end-to-end AI/ML pipeline for natural language processing with Amazon SageMaker.

You will learn how to:

• Ingest data into S3 using Amazon Athena and the Parquet data format
• Visualize data with pandas, matplotlib in Jupyter notebooks
• Run data bias analysis with SageMaker Clarify
• Perform feature engineering on a raw dataset using Scikit-Learn and SageMaker Processing Jobs
• Store and share features using SageMaker Feature Store
• Train and evaluate a custom BERT model using TensorFlow, Keras, and SageMaker Training Jobs
• Evaluate the model using SageMaker Processing Jobs
• Track model artifacts using Amazon SageMaker ML Lineage Tracking
• Run model bias and explainability analysis with SageMaker Clarify
• Register and version models using SageMaker Model Registry
• Deploy a model to a REST Inference Endpoint using SageMaker Endpoints
• Automate ML workflow steps by building end-to-end model pipelines using SageMaker Pipelines

**Pre-requisites**
Modern browser - and that's it!
Every attendee will receive a cloud instance
Nothing will be installed on your local laptop
Everything can be downloaded at the end of the workshop

**Location**
Online

Related Links
=============
O'Reilly Book: https://www.amazon.com/dp/1492079391/
Website: https://datascienceonaws.com
Meetup: https://meetup.datascienceonaws.com
GitHub Repo: https://github.com/data-science-on-aws/
YouTube: https://youtube.datascienceonaws.com
Slideshare: https://slideshare.datascienceonaws.com
Support: https://support.pipeline.ai

Past events (300)

Data Science on AWS Monthly Webinar: Advanced Analytics and AI/ML

Online Workshop - See Details Below

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