Date: 13th June 2019 | 3:00 pm – 4:00 pm
As organizations rush to innovate and modernize business with AI, one thing is clear. Just getting more insight in your business is no longer good enough but it needs fine-tuned foresight on what will happen next. At the heart of any prediction are production ready models that are trustworthy, explainable and fully traceable. Furthermore, the ability to augment your data science and business teams with AI productivity and automation features is vital to business success. And, you need a simplified way of preparing and shaping data, building and training models and deploying them into production.
Key Takeaways:
Augment your existing AI and data science practice with Auto AI / ML capabilities including auto data shaping, hyper parameter optimization, feature engineering, guided A/B testing and end-to-end flow improvement with Watson Machine Learning
Accelerate end-to-end AI life cycle management with Watson OpenScale to drive visibility, control and improvement of AI deployments
Help explain AI outcomes and scale AI usage with automated neural network design and deployments
Achieve virtually unlimited performance improvement in training and inference for your deep learning workloads with Watson Machine Learning Accelerator.
Start small and scale your AI deployment in a multi-tenant, elastic hybrid cloud
Speakers:
- Rohan Vaidyanathan, Lead Offering Manager, Watson OpenScale, IBM Data and AI
- Julianna DeLua, Subject Matter Expert and Product Marketer, IBM Data and AI
- Greg Filla, Senior Offering Manager, Data Scientist, IBM Data and AI
- Ser Yean Tan, Data Science Center of Excellence Leader – Asia Pacific, IBM Cloud