Sharpen Your Machine Learning Skills At Google Cloud Applied ML Summit

We see it throughout projects and commentaries across the broader technology industry. We see it in the amazing things our customers are doing, from creating friendly robots to aid childhood development, to leveraging data for better manufacturing and distribution, to fostering internal innovation through hackathons. And we see it in our own research and product development at Google, from improved machine learning models for our Speech API, to integrations that streamline data management and ML modeling, to making AlphaFold (DeepMind’s breakthrough protein structure prediction system) available to researchers throughout the world using VertexAI.

At Google Cloud, we’ve helped thousands of companies to accelerate their AI efforts, empower their data scientists, and extend the ability to build AI-driven apps and workflows to more people, including those without data science or ML expertise. Next month, we’ll take the next step in this journey with our customers, at Google Cloud Applied ML Summit.

Join us June 9 for this digital event, which will bring together some of the world’s leading ML and data science professionals to explore the latest cutting-edge AI tools for developing, deploying, and managing ML models at scale.

On-demand sessions kick off at 9:00 AM Pacific with “Accelerating the deployment of predictable ML in production,” featuring VP & GM of Google Cloud AI & Industry Solutions Andrew Moore; Google Cloud Developer Advocate Priyanka Vergadia; Ford Director of AI and Cloud Bryan Goodman; and UberAI Director of Engineering Smitha Shyam.

At the summit, you’ll learn how companies like General Mills, Vodafone, H&M, and CNA Insurance are developing, deploying, and safely managing long-running, self-improving AI services. Get insights in practitioner sessions where you can find new ways to:

• Build reliable, standardized AI pipelines across Spark on Google Cloud, Dataproc, BigQuery, Dataplex, Looker, and more, with a unified experience from Vertex AI, all in the session “Data to deployment – 5x faster.”

• Train high-quality ML models in minutes with AutoML innovations born of the latest Google Brain research, explored in the session “End-to-end AutoML for model prep.”

• Make the most of your Google Cloud investments in Vertex AI Training and Vertex AI Prediction to help you deploy custom models built on TensorFlow, PyTorch, scikit-learn, XGBoost, and other frameworks. Check out the session “ML prediction and serving: Vertex AI roadmap.”

• Automate and monitor AI integration, deployment, and infrastructure management to drive greater speed and efficiency. Don’t miss the session “Machine learning operations (MLOps) strategy and roadmap.”

• Streamline the process to audit, track, and govern ML models as they adapt to live data within a dynamic environment, without degrading performance. Dive into this topic  in the session “Model governance and auditability.”

You can choose from over a dozen sessions across three tracks: “Data to ML Essentials,” “Fact-track Innovation,” and “Self-improving ML.” Session topics range from MLOps best practices, to Google Cloud customer experiences, to the importance of model auditability, and explainable and responsible AI, with multiple customer panels and “ask me anything” sessions to help you get the insights and develop the skill to take your business’s ML efforts to the next level.

We’re committed to continuing to serve our customers in this rapidly-evolving space, and we’re excited to learn and collaborate with you at this event. To register, visit this link to reserve your seat for the Applied ML  Summit.