Lakehouse ML on Databricks Demo
Discover the latest innovations from Databricks that can help you build and operationalize the next generation of machine learning solutions. This demo will dive into Databricks Machine Learning, a data-centric AI platform that spans the full machine learning lifecycle – from data ingestion and model training to production MLOps. You’ll learn about key capabilities that […]
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AI Just Solved a 53-Year-Old Problem! | AlphaTensor, Explained
In a year where we’ve seen Artificial intelligence move forward in a significant way, AlphaTensor is the most exciting breakthrough we have accomplished. This video briefly introduces AlphaTensor and what it means for humanity.
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MLOps on Databricks: A How-To Guide
As companies roll out ML pervasively, operational concerns become the primary source of complexity. Machine Learning Operations (MLOps) has emerged as a practice to manage this complexity.
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How To Detect Silent Failures In ML Models
The webinar will teach you how to detect silent ML model failure without accessing the target data. We will cover the most likely causes for ML failure, like data and concept drift. You’ll learn the tools (both statistical and algorithmic) used in detecting and dealing with these failures, their applications, and their limits. By the […]
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Open Data Hub – the origin story (part 2)
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Frank
- July 6, 2022
- AI
- AI on Kubernetes
- Ai on OpenShift
- AI/ML
- artificial intelligence
- Data Science
- DevOps
- Git
- Jupyter
- JupyterHub
- JupyterLab
- Machine Learning
- ML
- ML on Kubernetes
- ML on OpenShift
- MLOps
- ODH
- Open Data Hub
- OpenShift
- OpenShift Data Science
- Python
- PyTorch
- Red Hat
- S2i
- Source-to-image
- Spark
- TensorFlow
In part 2 of the Open Data Hub origin story, fellow Red Hatters Steven Huels and Sherard Griffin describe some of the technical challenges and growth of the Open Data Hub AI meta-project, evolving Elastic Search to multiple data discovery technologies. The evolution to a commercial service offering, Red Hat OpenShift Data Science is also […]
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Open Data Hub – the origin story (part 1)
-
Frank
- July 6, 2022
- AI
- AI on Kubernetes
- Ai on OpenShift
- AI/ML
- artificial intelligence
- Data Science
- DevOps
- Git
- Jupyter
- JupyterHub
- JupyterLab
- Machine Learning
- ML
- ML on Kubernetes
- ML on OpenShift
- MLOps
- ODH
- Open Data Hub
- OpenShift
- OpenShift Data Science
- Python
- PyTorch
- Red Hat
- S2i
- Source-to-image
- Spark
- TensorFlow
Fellow Red Hatters Steven Huels and Sherard Griffin describe how the Open Data Hub meta-project grew from solving practical CI/CD build challenges to where it is today – providing an integrated blueprint stitching together over 20 open source AI tools for running large and distributed AI workloads on OpenShift. Part 1 of a 2 part […]
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Quick to Production with Minimal MLOps with the Best of Spark and TensorFlow
In this session, learn how we can get deep learning and ml models with TensorFlow into production quickly right after prototyping. Using TensorFlow with big datasets in a distributed setting has been an issue for small teams like ours due to complicated MLOps code, but with what we cover in the talk, we could now […]
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Accelerating MLOps with Kubernetes, CI/CD & GitOps
Artificial intelligence (AI)-powered applications are growing to deliver more mainstream experiences to users. Whether predicting rainfall and its effects on specific terrain or building a video game, AI models use machine learning (ML) to humanize the user experience in virtual or real world applications. Operationalizing these applications with integrated ML capabilities and keeping them up […]
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How to Implement Agile Workflows For Analytics and Machine Learning
Sprints, Scrum, Kanban, Stories, Epics, Retrospectives, Extreme Programming, Velocity…Agile’s opaque terminology and practices, plus the zeal of its advocates, can be off-putting to newcomers. Can it even be applied to data science, analytics and machine learning projects? In this talk we provide a gentle introduction to implementing an agile workflow for a data science team. […]
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High Level MLOps from Microsoft Data Scientists
On this episode of the AI Show, Seth welcomes Microsoft Data Scientists, Spyros Marketos, Davide Fornelli and Samarendra Panda. They will give a high-level intro into MLOps and share some of the lessons they’ve learned working with customers along the way.
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