Add more Feast descriptions in main README

adchia · adchia · commit e0f3bff7cb09 · 2022-05-16T19:15:44.000-04:00
Signed-off-by: Danny Chiao &lt;danny@tecton.ai&gt;
diff --git a/README.md b/README.md
@@ -6,14 +6,25 @@ This workshop aims to teach users about [Feast](http://feast.dev), an open-sourc
 
 We explain concepts & best practices by example, and also showcase how to address common use cases.
 
+### What is Feast?
+Feast is an operational system for managing and serving machine learning features to models in production. It can serve features from a low-latency online store (for real-time prediction) or from an offline store (for  batch scoring). 
+
 <img src="images/hero.png" width=600>
 
+### Why Feast?
+Feast solves several common challenges teams face:
+1. Feature reusability and model versioning across teams
+2. Training-serving skew and complex point-in-time-correct data joins
+3. Online feature availability
+
 ### Pre-requisites
 This workshop assumes you have the following installed:
 - A local development environment that supports running Jupyter notebooks (e.g. VSCode with Jupyter plugin)
 - Python 3.7+
 - pip
 - Docker & Docker Compose (e.g. `brew install docker docker-compose`)
+- Terraform ([docs](https://learn.hashicorp.com/tutorials/terraform/install-cli#install-terraform))
+- An AWS account setup with credentials(e.g see [AWS credentials quickstart](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-quickstart.html#cli-configure-quickstart-creds))
 
 Since we'll be learning how to leverage Feast in CI/CD, you'll also need to fork this workshop repository.
 
diff --git a/module_0/README.md b/module_0/README.md
@@ -37,11 +37,10 @@ We focus on a specific example (that does not include online features + models):
     - [Can I call `get_historical_features` without an entity dataframe? I want features for all entities.](#can-i-call-get_historical_features-without-an-entity-dataframe-i-want-features-for-all-entities)
 
 # Installing Feast
-Before we get started, first install Feast with AWS dependencies. Due to a bug in Feast 0.21, we'll also need s3fs for this tutorial to directly fetch from an S3 data source:
+Before we get started, first install Feast with AWS dependencies:
 
 ```bash
 pip install "feast[aws]"
-pip install s3fs
 ```
 
 # Reviewing Feast concepts
