RTX AI Software Pack is a perfect tool for

Deep Learning, Machine Learning, and Data Science. 

It can help you to:

- Speed up your workflow

- Accelerate data processing, model training, and visualization. 

- Works right out of the box for AI development. 

Generally, it takes 10 steps for DIY users to build an AI platform. For example, OS installation, CUDA installation, cuDNN, Python and TensorFlow installation, and then test and debug. A beginner may need to read around 400 pages of documents to understand the process. And you need to download these documents and software from different websites. It's really time-consuming and it will take you weeks or months before start your AI project.    

With RTX AI Software Pack, you can save your time to focus on your AI project instead of the platform preparation. 

RTX AI Software Pack is a full-stack GPU-accelerated software solution which have been tested and optimized for AI deployment. 

It incorporates the OS, GPU driver, CUDA, cuDNN library and deep learning and machine learning SDK. It's a full-stack package, so you don't need to collect drivers or SDK from different websites. 

We integrated 12 mainstream deep learning and machine learning framework, including the most familiar framework "Caffe",  most popular framework "TensorFlow" among enterprises, and "PyTorch" in education. In addition, RTX AI Software Pack also contain NVIDIA RAPIDS GPU-accelerated platform. In the past, GPU only benefit deep learning process. And now we can utilize GPU resources with RAPIDS to provides a much more swift workflow through GPU-accelerated data processing and increased model accuracy through faster iteration and more frequent deployment.

We also provide a system management tool "RTX AI System Utility". With this tool, you can check your software version or monitor GPU usage. And I’d like to highlight one key function is "system recovery".    System recovery function can provide you a clean AI environment in a snap, and you don't need to install all the software all over again from the beginning.

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