Update README.md

Author: kamranjk

README.md

@@ -5,71 +5,4 @@
 </table>
 
 
-The Xilinx Machine Learning (ML) Suite provides users with the tools to develop and deploy Machine Learning applications for Real-time Inference. It provides support for many common machine learning frameworks such as Caffe, Tensorflow, and MXNet.  
-
-<p align="left">
-  <img width="700" height="350" src="docs/img/stack.png">
-</p>
-
-The ML Suite is composed of three basic parts:
-1. **ML Framework and Open Source Support**  - Support for high level ML Frameworks and other open source projects.
-2. **xfDNN Middleware** - Software Library and Tools to Interface with ML Frameworks and optimize networks for Real-time Inference.
-3. **xDNN IP** - High Performance CNN processing engine.
-
-**Learn More:** [ML Suite Overview][]  
-**Watch:** [Webinar on Xilinx FPGA Accelerated Inference][]   
-**Forum:** [ML Suite Forum][]
-
-## [See What's New](docs/release-notes/1.x.md)
- - [Release Notes][]
- - Integration of Deephi DECENT Quantizer for TensorFlow
- - TensorFlow Jupyter Notebook
- - TensorFlow Command Line Examples
- - New precompiled Face Detection example applied to video
- - Ease of use enhancements
-    - Docker Images for both Caffe and Tensorflow
-    - Can run directly on the FPGA using Caffe or Tensorflow
- 
-## Getting Started
- - [Install XRT](docs/xrt.md) (Only necessary for On-Premise deployment)
- - [Start Docker Container](docs/container.md)
- - [Jupyter Notebook Tutorials](notebooks/README.md)
-   - [TensorFlow Image Classification](notebooks/image_classification_tensorflow.ipynb)
-   - [Caffe Image Classification](notebooks/image_classification_caffe.ipynb)
-   - [Caffe Object Detection w/ YOLOv2](notebooks/object_detection_yolov2.ipynb)
- - Command Line Examples
-   - [TensorFlow ImageNet Benchmark Models](examples/tensorflow/README.md)
-   - [Caffe ImageNet Benchmark Models](examples/caffe/README.md)
-   - [Caffe VOC SSD Example](examples/caffe/ssd-detect/README.md)
-   - [Deployment Mode Examples](examples/deployment_modes/README.md)
- - [In-Browser GoogLeNet Demo](apps/perpetual_demo/README.md)
- - [REST Server Example](examples/caffe/REST/README.md)
- - [Container Pipeline Example](docs/container_pipeline.md)
- 
-## References 
-- [ML Suite Overview][]  
-- [Performance Whitepaper][]
-- [Accuracy Benchmarks](examples/caffe/Benchmark_README.md)
-
-## [System Requirements](https://github.com/Xilinx/XRT/blob/master/src/runtime_src/doc/toc/system_requirements.rst)
-
-## Questions and Support
-- [FAQ][]
-- [ML Suite Forum][]
-- [AWS F1 Application Execution on Xilinx Virtex UltraScale Devices][]
-
-[models]: docs/models.md
-[Amazon AWS EC2 F1]: https://aws.amazon.com/marketplace/pp/B077FM2JNS
-[Xilinx Virtex UltraScale+ FPGA VCU1525 Acceleration Development Kit]: https://www.xilinx.com/products/boards-and-kits/vcu1525-a.html
-[AWS F1 Application Execution on Xilinx Virtex UltraScale Devices]: https://github.com/aws/aws-fpga/blob/master/SDAccel/README.md
-[SDAccel Forums]: https://forums.xilinx.com/t5/SDAccel/bd-p/SDx
-[Release Notes]: docs/release-notes/1.x.md
-[UG1023]: https://www.xilinx.com/support/documentation/sw_manuals/xilinx2017_4/ug1023-sdaccel-user-guide.pdf
-[FAQ]: docs/faq.md
-[ML Suite Overview]: docs/ml-suite-overview.md
-[Webinar on Xilinx FPGA Accelerated Inference]: https://event.on24.com/wcc/r/1625401/2D3B69878E21E0A3DA63B4CDB5531C23?partnerref=Mlsuite
-[ML Suite Forum]: https://forums.xilinx.com/t5/Xilinx-ML-Suite/bd-p/ML 
-[ML Suite Lounge]: https://www.xilinx.com/products/boards-and-kits/alveo/applications/xilinx-machine-learning-suite.html
-[Models]: https://www.xilinx.com/products/boards-and-kits/alveo/applications/xilinx-machine-learning-suite.html#gettingStartedCloud
-[whitepaper here]: https://www.xilinx.com/support/documentation/white_papers/wp504-accel-dnns.pdf
-[Performance Whitepaper]: https://www.xilinx.com/support/documentation/white_papers/wp504-accel-dnns.pdf
+Xilinx ML Suite is now deprecated. Please use [Vitis AI](https://github.com/Xilinx/Vitis-AI) in the place of ML Suite and for all AI acceleration on Xilinx platforms.