AI Analytics Part 1: Optimize End-to-End Data Science and Machine Learning Acceleration

In This Series:

AI Analytics Part 2: Enhance Deep Learning Workloads on 3rd Generation Intel® Xeon® Scalable Processors

AI Analytics Part 3: Walk through the Steps to Optimize End-to-End Machine Learning Workflows

It is an AI world, with nearly every global industry applying AI to new (and old) processes, use cases, and applications. The opportunities are endless, as are the competitive advantages that come with AI-based software solutions optimized for potent hardware.

If you are a data scientist, developer, or researcher, the machinations of AI are your playground—machine learning and deep learning workloads, training deep neural networks, and integrating trained models into applications for inference.

Which is why this webinar is for you. (And, in fact, the entire three-part series.)

Its focus: The Intel® AI Analytics Toolkit (AI Kit), a powerful set of familiar Python* tools to accelerate each step in the AI application pipeline.

In Part 1 of a three-part series, join Saumya Satish—product manager for AI Products—to learn how the AI Kit delivers drop-in acceleration for Intel architectures, helping you drastically improve productivity while achieving top-model accuracy.

Saumya, together with software engineer Lance Atencio, cover:

• An overview of the AI Kit and its developer benefits
• How to accelerate data science and machine learning workflows
• How to perform model training and inference on Intel architectures
• How to optimize the Python data science tool chain with minimal code changes and run end-to-end workloads right out of the box

Download the Intel® AI Analytics Toolkit for Linux*

Learn More

• Read the latest AI Analytics blogs on Medium.
• Develop in the Cloud—Sign up for an Intel® Developer Cloud account, a free development sandbox with access to the latest Intel hardware and oneAPI software.
• Subscribe to the POD—Code Together is an interview series that explores the challenges at the forefront of cross-architecture development. Each biweekly episode features industry VIPs who are blazing new trails through today's data-centric world. Listen and subscribe today.
  • Alexa* (Say “Alexa, play the podcast Code Together”)
  • iTunes*
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  • TuneIn

Saumya Satish
Product marketing engineer, Intel Corporation

Saumya is a product manager for AI software products, with a focus on deep learning and data analytics technologies. She is passionate about the developer ecosystem and keen to provide the right set of tools that help developers build innovative applications, particularly AI and machine learning domains. Since joining Intel in 2011, she has worked as a research scientist and technical evangelist on some of Intel's imaging and computer vision software products. Saumya holds a master's degree in electrical engineering from University of Florida, Gainesville. A native of India, she is based in San Jose, California.

Lance Atencio
Software applications engineer, Intel Corporation

Lance has over 30 years of experience in a wide variety of edge-to-cloud software development roles–from developing applications and solutions to customer consulting. Joining Intel in 2000, his most recent work focuses on deep learning and discrete GPUs. Lance holds a bachelor's degree in electrical engineering and a master's degree in computer science from the University of New Mexico.