diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -1,44 +1,47 @@
-
+
+ 
+
+
-# Archai: Platform for Neural Architecture Search
+
+ Archai accelerates your Neural Architecture Search (NAS) through fast, reproducible and modular research, allowing you to generate efficient deep networks for your applications.
+
-[](https://github.com/microsoft/archai/blob/main/LICENSE)
-[](https://github.com/microsoft/archai/issues)
-[](https://github.com/microsoft/archai/releases)
+
-**Archai** is a Neural Network Search (NAS) platform that allows you to generate efficient deep networks for your applications. It offers the following advantages:
+
-* 🔬 Easy mix-and-match between different algorithms;
-* 📈 Self-documented hyper-parameters and fair comparison;
-* âš¡ Extensible and modular to allow rapid experimentation;
-* 📂 Powerful configuration system and easy-to-use tools.
+
-Please refer to the [documentation](https://microsoft.github.io/archai) for more information.
-
-Package compatibility: **Python 3.7+** and **PyTorch 1.2.0+**.
-
-OS compatibility: **Windows**, **Linux** and **MacOS**.
-
-## Table of contents
-
- * [Quickstart](#quickstart)
- * [Installation](#installation)
- * [Running an Algorithm](#running-an-algorithm)
- * [Tutorials](#tutorials)
- * [Support](#support)
- * [Contributions](#contributions)
- * [Team](#team)
- * [Credits](#credits)
- * [License](#license)
- * [Trademark](#trademark)
+
## Quickstart
-### Installation
+To run a specific NAS algorithm, specify it by the `--algos` switch:
+
+```terminal
+python scripts/main.py --algos darts --full
+```
+
+Please refer to [running algorithms](https://microsoft.github.io/archai/user-guide/tutorial.html#running-existing-algorithms) for more information on available switches and algorithms.
+
+## Installation
There are many alternatives to installing Archai, but note that regardless of choice, we recommend using it within a virtual environment, such as `conda` or `pyenv`.
-#### PyPI
+### PyPI
PyPI provides a fantastic source of ready-to-go packages, and it is the easiest way to install a new package:
@@ -46,7 +49,7 @@ PyPI provides a fantastic source of ready-to-go packages, and it is the easiest
pip install archai
```
-#### Source (development)
+### Source (development)
Alternatively, one can clone this repository and install the bleeding-edge version:
@@ -58,17 +61,7 @@ install.sh # on Windows, use install.bat
Please refer to the [installation guide](https://microsoft.github.io/archai/getting-started/install.html) for more information.
-### Running an Algorithm
-
-To run a specific NAS algorithm, specify it by the `--algos` switch:
-
-```terminal
-python scripts/main.py --algos darts --full
-```
-
-Please refer to [running algorithms](https://microsoft.github.io/archai/user-guide/tutorial.html#running-existing-algorithms) for more information on available switches and algorithms.
-
-### Tutorials
+## Examples
The best way to familiarize yourself with Archai is to take a quick tour through our [30-minute tutorial](https://microsoft.github.io/archai/user-guide/tutorial.html). Additionally, one can dive into the [Petridish tutorial](https://microsoft.github.io/archai/user-guide/petridish.html) developed at Microsoft Research and available at Archai.
@@ -76,8 +69,14 @@ We highly recommend [Visual Studio Code](https://code.visualstudio.com) to take
On the other hand, you can use [Archai on Azure](tools/azure/README.md) to run NAS experiments at scale.
+## Documentation
+
+Please refer to the [documentation](https://microsoft.github.io/archai) for more information.
+
## Support
+Archai has been created and maintained by [Shital Shah](https://shital.com), [Debadeepta Dey](www.debadeepta.com), [Gustavo de Rosa](https://www.microsoft.com/en-us/research/people/gderosa), Caio Mendes, [Piero Kauffmann](https://www.microsoft.com/en-us/research/people/pkauffmann/), and [Ofer Dekel](https://www.microsoft.com/en-us/research/people/oferd) at Microsoft Research.
+
### Contributions
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.
@@ -86,20 +85,16 @@ When you submit a pull request, a CLA-bot will automatically determine whether y
This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or contact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.
-## Team
-
-Archai has been created and maintained by [Shital Shah](https://shital.com), [Debadeepta Dey](www.debadeepta.com), [Gustavo de Rosa](https://www.microsoft.com/en-us/research/people/gderosa), Caio Mendes, [Piero Kauffmann](https://www.microsoft.com/en-us/research/people/pkauffmann/), and [Ofer Dekel](https://www.microsoft.com/en-us/research/people/oferd) at Microsoft Research.
-
### Credits
Archai builds on several open-source codebases. These includes: [Fast AutoAugment](https://github.com/kakaobrain/fast-autoaugment), [pt.darts](https://github.com/khanrc/pt.darts), [DARTS-PyTorch](https://github.com/dragen1860/DARTS-PyTorch), [DARTS](https://github.com/quark0/darts), [petridishnn](https://github.com/microsoft/petridishnn), [PyTorch CIFAR-10 Models](https://github.com/huyvnphan/PyTorch-CIFAR10), [NVidia DeepLearning Examples](https://github.com/NVIDIA/DeepLearningExamples), [PyTorch Warmup Scheduler](https://github.com/ildoonet/pytorch-gradual-warmup-lr), [NAS Evaluation is Frustratingly Hard](https://github.com/antoyang/NAS-Benchmark), [NASBench-PyTorch](https://github.com/romulus0914/NASBench-PyTorch).
Please see `install_requires` section in [setup.py](https://github.com/microsoft/archai/blob/master/setup.py) for up-to-date dependencies list. If you feel credit to any material is missing, please let us know by filing an [issue](https://github.com/microsoft/archai/issues).
-### License
-
-This project is released under the MIT License. Please review the [file](https://github.com/microsoft/archai/blob/master/LICENSE) for more details.
-
### Trademark
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.
+
+### License
+
+This project is released under the MIT License. Please review the [file](https://github.com/microsoft/archai/blob/master/LICENSE) for more details.
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