Solving a data science problem usually requires multiple steps. These steps can include extracting and transforming data, training a model, and deploying the model into production. In this session, we'll discuss how to specify those steps with Python into an ML pipeline. We'll show how to create a Kubeflow Pipeline, a component of the Kubeflow open-source project. The audience will learn about how to integrate TensorFlow Extended components into the pipeline, and how to deploy the pipeline to the hosted Cloud AI Pipelines environment on Google Cloud. The key takeaway is how to improve reuse and reproducibility of the machine learning process.
Get started with your machine learning adventures by using state-of-the-art tools. We will talk about how to utilize the amazing work done by others to jump start your projects. We will also talk about making them more scalable and getting to a solution that can be used for production as well.
Discover how to achieve superpowers by embracing machine learning in JavaScript using TensorFlow.js in the browser and beyond in this speedy 45 minute talk. Get inspired through a whole bunch of creative prototypes that push the boundaries of what is possible in the modern web browser and then take your own first steps with machine learning in minutes. By the end of the talk everyone will understand how to recognize an object of their choice which could then be used in any creative way you can imagine. Familiarity with JavaScript is advantageous, but no background in machine learning is required. Come take your first steps with TensorFlow.js!
This talk provides an overview of TensorFlow Lite and its awesome tools and resources to help you create intelligent apps. I will walk through end-to-end computer vision examples with TFLite: from model training, conversion, optimization to model deployment on mobile and edge devices.
Coral is a complete toolkit to build products with local AI. Our on-device inferencing capabilities allow you to build products that are efficient, private, fast and offline. In this talk, we will introduce Coral and walk participants through current applications. In the second part, we will do some hands on demos to run inference using Coral devices.
