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Study mode:
on
1
intro
2
preamble
3
agenda
4
airflow
5
challenges when creating genai pipelines
6
key airflow features for genai
7
taskflow api - airflow decorators
8
automatic retries in airflow
9
branching in airflow
10
deferrable operators
11
dataset scheduling
12
datasets in the airflow 2.9 ui
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advanced dataset scheduling
14
dynamic task mapping
15
demo repo: content generation
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astro
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take home message
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a comprehensive conference talk on building a GenAI pipeline for content generation using Apache Airflow. Dive into the challenges of creating GenAI pipelines and discover key Airflow features that address these issues. Learn about the TaskFlow API, automatic retries, branching, deferrable operators, dataset scheduling, and dynamic task mapping. Follow along with a detailed demo of a content generation repository and gain insights into Astro, a managed Airflow service. Walk away with practical knowledge on leveraging Apache Airflow for efficient GenAI pipeline development and management.

GenAI Pipeline for Content Generation with Apache Airflow

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