AI Analytics PART 1: Optimize End-to-End Data Science and Machine Learning Acceleration
The field of Artificial Intelligence is now a senior citizen (it was formally founded in 1956). But its gains and innovations—driven by optimized software applications—continue to be new and amazing. In this first-of-three session, learn why the Intel AI Analytics Toolkit should be part of every AI developer’s toolbelt.
It’s an AI world, with nearly every global industry applying artificial intelligence 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’re a data scientist, developer, or researcher, the machinations of AI are your playground—ML/DL workloads, training deep neural networks, integrating trained models into apps for inference.
Which is why this webinar is for you. (And, in fact, the entire 3-part series.)
Its focus: The Intel® AI Analytics Toolkit (aka AI Kit), a powerful set of familiar Python tools to accelerate each step in the AI application pipeline.
In Part 1 of a 3-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, will cover:
- An overview of the AI Kit and its developer benefits
- How to accelerate data science and machine learning workflows
- How to 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
Save your spot now.