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Nov 01

No sessions scheduled.

Nov 03

No sessions scheduled.

Nov 04

11:00

CloudNews

Luca Cavallin, Jacco Kulman
In these live episode of Club Cloud Stories - The Cloud News, hosts Jacco and Luca discuss the latest cloud developments from Amazon Web Services and Google Cloud Platform.
Technologies: AWS Google Cloud
Topics:
15:00

Infrastructure-as-Code Workshop

Luca Cavallin, Niels van Doorn
An infrastructure-as-code workshop where you have the opportunity to go hands-on with Teraform and Google Cloud Run.
Technologies: Google Cloud
Topics: Infrastructure as Code
18:00

Google Data mesh and streaming data ingestion

Navin Goel
Technologies: Google Cloud
Topics: Data & AI
19:00

Google Vertex AI

Wouter Roosenburg
Vertex AI is a unified MLOps platform to help data scientists/ML engineers increase experimentation, deploy faster, and manage models with confidence. Vertex AI brings together the Google Cloud services for building ML under one, unified UI and API. In Vertex AI, you can now easily train and compare models using AutoML or custom code training and all your models are stored in one central model repository. One AI platform, every ML tool you need A unified UI for the entire ML workflow Vertex AI brings together the Google Cloud services for building ML under one, unified UI and API. In Vertex AI, you can now easily train and compare models using AutoML or custom code training and all your models are stored in one central model repository. These models can now be deployed to the same endpoints on Vertex AI. Pre-trained APIs for vision, video, natural language, and more Easily infuse vision, video, translation, and natural language ML into existing applications or build entirely new intelligent applications across a broad range of use cases (including Translation and Speech to Text). AutoML enables developers to train high-quality models specific to their business needs with minimal ML expertise or effort. With central managed registry for all datasets across data types (vision, natural language, and tabular). End-to-end integration for data and AI You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI for seamless integration across the data-to-AI life cycle. Use Vertex Data Labeling to generate highly accurate labels for your data collection. Support for all open source frameworks Vertex AI integrates with widely used open source frameworks such as TensorFlow, PyTorch, and scikit-learn, along with supporting all ML frameworks via custom containers for training and prediction.
Technologies: Google Cloud
Topics: Data & AI
20:00

Modernise with Anthos – Google Cloud

Rushil Sharma
Outdated systems restrict savings, speed, and freedom from proprietary software. With Anthos, you can modernize your apps with containerized microservices and VMs to innovate faster and deliver more to your customers. Build across environments with containers With Migrate for Anthos and GKE, you can avoid vendor lock-in and achieve immediate operational cost savings, enhanced agility and flexibility, and extended application life spans. Faster modernization on a single application platform Modernize up to 75% faster with lower operational cost by migrating to containers without rewriting. Build and deploy apps faster at scale on a single secure platform to manage apps across environments. Increase developer productivity With Anthos, you can adopt agile DevOps practices and ship code faster with a consistent experience and API wherever you’re operating. Your developers can focus on writing, testing, and pushing code.
Technologies: Google Cloud
Topics: Software Engineering

Nov 05

No sessions scheduled.