Every day brings new and advanced AI development tools for everything from advanced algorithms in adaptive learning and neural networks to hardware optimized libraries for GPUs and TPUs. However, these vast array of technologies can become challenging to navigate for those interested in building AI capabilities into their applications.
In this workshop we show how to build effective AI services for your applications. We will run through several use cases of numerical and text analysis data - from the beginning of raw data to a fully deployed and managed AI service in the cloud - with all the steps in between (data preparation, feature engineering, model training, model validation, deployment, application integration and monitoring). You will also learn how to assess whether AI is helping your business application and how to manage and tune your new AI feature over time. We will use AWS as the base for our exercises. All datasets are public and will be provided for the participants access.
founder of Pyxeda AI. Previously, Nisha co-founded ParallelM which pioneered the MLOps practice of managing machine learning in production. Nisha is a recognized leader in the operational machine learning space. Nisha was previously a Fellow at SanDisk and Fellow/Lead Architect at Fusion-io, where she worked on innovation in non-volatile memory technologies and applications.