NVIDIA GPU For End-To-End Machine Learning Acceleration (Link In Description)

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Manyata Tech Park

Manyata Tech Park Road · Bengaluru

How to find us

L-6, 8th Floor, NVIDIA Office

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Details

Do you want to learn how to use an NVIDIA GPU to accelerate your AI tasks? Analytics India Magazine has teamed up with NVIDIA to bring to data scientists a workshop focused on tools they need for GPU acceleration. Attendees will be able to learn how to implement GPU acceleration in everyday ML and DL tasks. The workshop will be held at NVIDIA's office in Manyata Tech Park, Bengaluru.

PLEASE FILL THE APPLICATION FORM: https://bit.ly/2X87JT6

Agenda for the meetup: Accelerating ML and DL tasks using NVIDIA's cloud-based end-to-end accelerated stack of software.

The Keynote Speaker for this workshop is Sundara Ramalingam Nagalingam, Head, Deep Learning Practice, NVIDIA Graphics Pvt Ltd.

The workshop will take the participants through the following topics:
>Accelerated Data Analytics for Better Insight & Use Cases
>RAPIDS Deep Dive
>Accelerating Data Science End-to-End with GPU & Getting Started with >NVIDIA GPU Cloud
>Data ETL Pipelining Hands-on with cuDF
>XGBoost on MultiGPU Demo and Discussion
>Running other Algorithms on GPU Hands-on
>Q&A Session

PLEASE FILL THE APPLICATION FORM: https://bit.ly/2X87JT6

Who Should Attend?
>Data Engineers & Data Scientists looking to supercharge their training and inference workflows
>Data Science managers looking for an upgrade to existing infrastructure
>AI/ML enthusiasts with experience in basic concepts of ML, data science, workflows and have worked with Python, Scikit-learn, or Pandas

GPU computing has become one of the most important parts of AI infrastructure today. Owing to inherent architectural advantages present in the card, GPUs are the best fit for accelerating Deep Learning tasks.

PLEASE FILL THE APPLICATION FORM: https://bit.ly/2X87JT6

In addition to hardware for parallel procession, NVIDIA provides a cloud based end to end accelerated stack of software, which includes CUDA, CUDA X libraries, drivers, frameworks and much more.

Most prominent DL frameworks, such as TensorFlow, PyTorch, Caffe2, PaddlePaddle and more natively support NVIDIA GPU acceleration for heavy workloads.

So do apply soon and be part of this exciting workshop along with your friends and colleagues who are also interested in Analytics / Data Science acceleration using GPUs.

PLEASE FILL THE APPLICATION FORM: https://bit.ly/2X87JT6