12:20 | 13:00
Augmenting your services and application capabilities with Machine Learning is part of the mission of Google Cloud: democratize AI by opening its capabilities to every developer worldwide. In Google we are unlocking this potential with Open Source frameworks like TensorFlow, next-gen Kubernetes-based platforms for model portability like Kubeflow, or end-to-end solutions like AutoML, a self-training engine to accomodate the full lifecycle of an ML model.
What challenges can we face when creating a Data processing pipeline? How can we go from Zero to ML? What are the tools in Google’s AI platform and how to best apply them?
We will discover this and more in this technical journey through Google Cloud’s Data / ML solutions