Update README.md

Author: ospillinger

README.md

@@ -4,29 +4,25 @@
 
 **Get started:** [Install](https://docs.cortex.dev/install) • [Tutorial](https://docs.cortex.dev/tutorial) • [Demo Video](https://www.youtube.com/watch?v=vcistUor0b4) • <!-- CORTEX_VERSION_MINOR_STABLE e.g. https://docs.cortex.dev/v/0.2/ -->[Docs](https://docs.cortex.dev) • <!-- CORTEX_VERSION_MINOR_STABLE -->[Examples](https://github.com/cortexlabs/cortex/tree/0.3/examples)
 
-**Learn more:** [Website](https://cortex.dev) • [FAQ](https://docs.cortex.dev/faq) • [Subscribe](https://cortexlabs.us20.list-manage.com/subscribe?u=a1987373ab814f20961fd90b4&id=ae83491e1c) • [Blog](https://medium.com/cortex-labs) • [Contact](mailto:hello@cortex.dev)
+**Learn more:** [Website](https://cortex.dev) • [FAQ](https://docs.cortex.dev/faq) • [Blog](https://blog.cortex.dev) • [Subscribe](https://cortexlabs.us20.list-manage.com/subscribe?u=a1987373ab814f20961fd90b4&id=ae83491e1c) • [Twitter](https://twitter.com/cortex_deploy) • [Contact](mailto:hello@cortex.dev)
 
 <br>
 
-**Machine learning infrastructure for developers:** build and deploy scalable TensorFlow applications on AWS without worrying about setting up infrastructure, managing dependencies, or orchestrating data pipelines.
-
-Cortex is actively maintained by Cortex Labs. We're a venture-backed team of infrastructure engineers and [we're hiring](https://angel.co/cortex-labs-inc/jobs).
+**Machine learning pipelines as code:** deploy machine learning applications without worrying about setting up infrastructure, managing dependencies, or orchestrating data pipelines.
 
 <br>
 
 ## How it works
 
-#### Data validation: validate data to prevent data quality issues early
+1. **Define your app:** define your app using Python, TensorFlow, and PySpark.
 
-```yaml
-- kind: raw_column
-  name: col1
-  type: INT_COLUMN
-  min: 0
-  max: 10
-```
+2. **`$ cortex deploy`:** deploy end-to-end machine learning pipelines to AWS with one command.
+
+3. **Serve predictions:** serve real time predictions via horizontally scalable JSON APIs.
+
+## End-to-end machine learning workflow
 
-#### Data ingestion: connect to your data warehouse and ingest data at scale
+**Data ingestion:** connect to your data warehouse and ingest data.
 
 ```yaml
 - kind: environment
@@ -37,7 +33,7 @@ Cortex is actively maintained by Cortex Labs. We're a venture-backed team of inf
     schema: [@col1, @col2, ...]
 ```
 
-#### Data transformation: use custom Python and PySpark code to transform data at scale
+**Data transformation:** use custom Python and PySpark code to transform data.
 
 ```yaml
 - kind: transformed_column
@@ -46,7 +42,7 @@ Cortex is actively maintained by Cortex Labs. We're a venture-backed team of inf
   input: @col1
 ```
 
-#### Model training: train models with custom TensorFlow code
+**Model training:** train models with custom TensorFlow code.
 
 ```yaml
 - kind: model
@@ -61,7 +57,7 @@ Cortex is actively maintained by Cortex Labs. We're a venture-backed team of inf
     num_steps: 10000
 ```
 
-#### Prediction serving: deploy models as prediction APIs that scale horizontally
+**Prediction serving:** serve real time predictions via JSON APIs.
 
 ```yaml
 - kind: api
@@ -71,7 +67,7 @@ Cortex is actively maintained by Cortex Labs. We're a venture-backed team of inf
     replicas: 3
 ```
 
-#### Deploying to AWS: deploy your pipeline to AWS and make prediction requests
+**Deployment:** Cortex deploys your pipeline on scalable cloud infrastructure.
 
 ```
 $ cortex deploy
@@ -86,10 +82,10 @@ Ready! https://abc.amazonaws.com/my-api
 
 ## Key features
 
-- **End-to-end machine learning workflow:** Cortex spans the machine learning workflow from feature management to model training to prediction serving.
-
 - **Machine learning pipelines as code:** Cortex applications are defined using a simple declarative syntax that enables flexibility and reusability.
 
+- **End-to-end machine learning workflow:** Cortex spans the machine learning workflow from feature management to model training to prediction serving.
+
 - **TensorFlow and PySpark support:** Cortex supports custom [TensorFlow](https://www.tensorflow.org) code for model training and custom [PySpark](https://spark.apache.org/docs/latest/api/python/index.html) code for data processing.
 
 - **Built for the cloud:** Cortex can handle production workloads and can be deployed in any AWS account in minutes.