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Even as AI technologies move into common use, many enterprise decision makers remain baffled about what the different technologies actually do and how they can be integrated into their businesses. Rather than focusing on the technologies alone, Kristian Hammond provides a practical framework for understanding your role in problem solving and decision making.

In this day-long presentation, you'll walk through the process of building a complete machine learning pipeline, from ingest and exploration to training, evaluation, deployment, and prediction.

Kubernetes—the container orchestration engine used by all of the top technology companies—was built from the ground up to run and manage highly distributed workloads on huge clusters. Thus, it provides a solid foundation for model development. Daniel Whitenack demonstrates how to easily deploy and scale AI/ML workflows on any infrastructure using Kubernetes.

David Arpin offers an overview of the Amazon SageMaker machine learning platform, walking you through setup and using Amazon SageMaker Notebook (a hosted Jupyter Notebook server). You'll get hands-on experience with SageMaker's built-in deep learning algorithm as you dive into building your own neural network architecture using SageMaker's prebuilt TensorFlow containers.

Carl Osipov walks you through creating increasingly sophisticated image classification models using TensorFlow.

From social network photo filters to self-driving cars, computer vision has brought applied deep learning to the masses. Built by the pioneers of computer vision software, PyTorch enables developers to rapidly build computer vision models. Mo Patel and David Mueller offer an overview of computer vision fundamentals and walk you through using PyTorch to build computer vision applications.

Ray is a new distributed execution framework for reinforcement learning applications. Ion Stoica, Robert Nishihara, and Philipp Moritz lead a deep dive into Ray, walking you through its API and system architecture and sharing application examples, including several state-of-the-art reinforcement learning algorithms.

From open data marketplaces to privacy-preserving computation, explore how blockchain technologies are enabling a new arc of development in AI and machine learning.

Purpose, a well-defined problem, and trust from people are important factors to any system, especially those that employ AI. Chris Butler leads you through exercises that borrow from the principles of design thinking to help you create more impactful solutions and better team alignment.

Utilizing AI technologies to advance business goals remains one of the most daunting challenges for many business leaders. Beth Partridge, assisted by Nick Paquin and Annie O'Connor, shares a breakthrough approach that bridges the gap between data science and business. Join in to gain a clear understanding of what AI can do for your business and how to go about implementing it.

High-resolution land cover maps help quantify long-term trends like deforestation and urbanization but are prohibitively costly and time intensive to produce. Mary Wahl and Banibrata De demonstrate how to use Microsoft’s Cognitive Toolkit and Azure cloud resources to produce land cover maps from aerial imagery by training a semantic segmentation DNN—both on single VMs and at scale on GPU clusters.

Xiaoyong Zhu, Gheorghe Iordanescu, Wilson Lee, and Ivan Tarapov walk you through building a deep learning model and intelligent applications on edge devices running iOS, Android, and Windows, using a working example that helps clinicians in areas with less access to radiologists identify possible lung diseases.

Get to know your fellow attendees over dinner. We've made reservations for you at some of the most sought-after restaurants in town. This is a great chance to make new connections and sample some of the great cuisine San Francisco has to offer.

What new companies are at the leading edge of the AI space? Meet some of the best, most innovative founders as they demonstrate their game-changing ideas at the Startup Showcase.