This webinar is a must attend if you or your customers are challenged by inability to do Machine Learning in production. We'll present a solution to develop ML models, train them, manage features and push to production on a continuous basis.
Explore the business drivers and use cases of MLOps including Vertex.ai, ML pipelines, CI/CD, labeling and inference. Discover the the best path to improve the efficiency of your data science and data engineers.
Don’t miss this opportunity to grow your understanding of MLOps tools and their impact on customer production. Also learn more about Bitstrapped’s solution for MLOps — MLOps Foundation.
- Review the painpoints for deploying ML in production
- Introduce Machine Learning Operations (MLOps), why does it exist, and what does it solve for
- Explore what tools does Google Cloud offer for AI/ML
- Learn how to deploy Vertex.ai
- Learn how to apply these products and tools to accomplish my business goals
- Hear about examples of industry solutions
- Introduction to MLOps, business drivers, and our solution for ML in production - Vertex.ai
- Review an end-to-end MLOps essentials use cases
Chief Technology Officer