AWS ML Dev Day - End-to-End Amazon SageMaker Pipeline with BERT - June 2021
Build an End-To-End Pipeline With BERT, Tensorflow, and Amazon SageMaker
June 28, 2021 | 9:00 AM - 1:00 PM PT
About the Workshop
In this hands-on workshop, we will build an end-to-end AI/ML pipeline for natural language processing with Amazon SageMaker. This workshop will dive deep into the selected topic. Presenters assume the audience has some familiarity with the topic, but may or may not have direct experience implementing a similar solution. Presenters will dive into code, cover advanced tricks, and explore future developments in the technology.
Attendees will learn how to:
Ingest data into S3 using Amazon Athena and the Parquet data format
Visualize data with pandas and matplotlib on SageMaker 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
Who Should Attend
Data scientists and machine learning practitioners with a working knowledge of machine learning algorithms and concepts, who are proficient in Python programming at an intermediate level, and who are familiar with Jupyter notebooks and statistics.
Welcome, Introductions, and Demo Setup
9:00 AM - 9:30 AM PT
Ingest and Explore Data
9:30 AM - 10:00 AM PT
Analyze Data for Bias
10:00 AM - 10:30 AM PT
BERT Feature Engineering
10:30 AM - 11:00 AM PT
BERT Fine-Tuning
11:15 AM - 11:45 AM PT
Build an End-to-End BERT Text Classifier Pipeline
11:45 AM - 12:15 PM PT
Analyze Model for Bias and Explainability
12:15 PM - 12:45 PM PT
Register and Deploy Model
12:45 PM - 1:00 PM PT
AWS Cloud Concepts
Presenters assume a working knowledge of AWS cloud concepts, familiarity with AWS SDKs as well as the AWS Management Console.
Data Science Tools
Presenters assume a working knowledge of machine learning algorithms and concepts, proficiency in Python programming at an intermediate level, and familiarity with Jupyter notebooks and statistics.
![[WORKSHOP] Generative AI and Large Language Models: Fine-tuning with SageMaker + PEFT + RLHF + PPO](https://images.videosashka.com/watch/fLPNMleobgY)
