Readme update for package renaming changes

Author: dhavalsalwala

README.md

@@ -1,8 +1,8 @@
-# SAIL
+# AUTOSAIL
 
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) ![main branch](https://github.com/IBM/autosail/actions/workflows/build.yml/badge.svg?branch=main) [![](https://img.shields.io/badge/python-3.10-blue.svg)](https://www.python.org/downloads/) <img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
 
-The library is for experimenting with streaming processing engines (SPEs) and incremental machine learning (IML) models. The main features of Sail are:
+The library is for experimenting with streaming processing engines (SPEs) and incremental machine learning (IML) models. The main features of AutoSail are:
 
 - Common interface for all incremental models available in libraries like Scikit-Learn, Pytorch, Keras and River.
 - Distributed computing for model selection, ensembling etc.
@@ -12,37 +12,37 @@ The library is for experimenting with streaming processing engines (SPEs) and in
 
 ## Documentation
 
-See the [**SAIL Wiki**](https://github.com/IBM/autosail/wiki) for full documentation, installation guide, operational details and other information.
+See the [**AutoSAIL Wiki**](https://github.com/IBM/autosail/wiki) for full documentation, installation guide, operational details and other information.
 
 ## Architecture
 
-### SAIL Pipeline
+### AutoSAIL Pipeline
 
 ![Architecture](architecture.png)
 
-### SAIL Model Framework
+### AutoSAIL Model Framework
 
 ![Architecture](model_framework.png)
 
 ## Difference with River and other existing incremental machine learning libraries.
 
-Sail leverages the existing machine learning libraries like River, sklearn etc and creates a common set of APIs to run these models in the backend. In particular, while River provides minimal utilities for deep learning models, it does not focus on deep learning models developed through Pytorch and Keras. In addition, models in Sail are parallelized using Ray. The parallelization results in three major advatages that are particularly important for incremental models with high volume and high velocity data:
+AutoSAIL leverages the existing machine learning libraries like River, sklearn etc and creates a common set of APIs to run these models in the backend. In particular, while River provides minimal utilities for deep learning models, it does not focus on deep learning models developed through Pytorch and Keras. In addition, models in AutoSAIL are parallelized using Ray. The parallelization results in three major advatages that are particularly important for incremental models with high volume and high velocity data:
 
 - Faster computational times for ensemble models.
 - Faster computational times for ensemble of forecasts.
 - Creates a clean interface for developing AutoML algorithms for incremental models.
 
 ## Spark vs Ray for incremental models.
 
-Sail could have been parallelized using Spark as well. However, to keep the streaming processing engines and machine learning tasks independent, Ray was preferred as the data can then be handled using Pandas, Numpy etc efficiently. This flexibility further allows using other SPEs like Flink or Storm without updating the parallelization framework for IML models.
+AutoSAIL could have been parallelized using Spark as well. However, to keep the streaming processing engines and machine learning tasks independent, Ray was preferred as the data can then be handled using Pandas, Numpy etc efficiently. This flexibility further allows using other SPEs like Flink or Storm without updating the parallelization framework for IML models.
 
 ## 🛠 Installation
 
-Sail is intended to work with **Python 3.8 and above**. You can install the latest version from GitHub as so:
+AutoSAIL is intended to work with **Python 3.8 and above**. You can install the latest version from GitHub as so:
 
 ```sh
 git clone https://github.com/IBM/autosail.git
-cd sail
+cd autosail
 pip install -e ".[OPTION]"
 ```
 
@@ -69,7 +69,7 @@ pip install -e ".[examples]"
 
 ## Recognition
 
-SAIL has been identified as innovations with market potential that can contribute to UN Sustainable Development Goals by the European Commission Innovation Radar. More details [here](https://innovation-radar.ec.europa.eu/innovation/46749).
+AUTOSAIL has been identified as innovations with market potential that can contribute to UN Sustainable Development Goals by the European Commission Innovation Radar. More details [here](https://innovation-radar.ec.europa.eu/innovation/46749).
 
 ## Acknowledgment