Join Josh Mesout and Rishit Dagli in our in-depth workshop on Kubeflow as a Service, aimed at demystifying the deployment of machine learning models using open-source tools.
This Civo Navigate 24 session caters to participants of all skill levels in machine learning, Kubernetes, and ML infrastructure. It covers foundational aspects of Kubeflow, dives into advanced tools like Llama 2 and Kerve, and showcases how to use these models as cost-effective alternatives to services like ChatGPT.
Whether you're spearheading a startup or planning to scale, this workshop provides essential knowledge for leveraging machine learning efficiently and economically.
Follow the full workshop with our github repo -► https://github.com/civo-learn/kubeflo...
Learn more about Civo Navigate here -►https://www.civo.com/navigate
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0:00 - Introduction and Welcome
0:18 - Overview of Kubeflow as a Service
1:04 - Introduction to Civo's Machine Learning Platform
2:08 - Discussion on Open Source and Accessibility
2:39 - Introduction of Speakers and Background
3:51 - Coding Demonstration: Setting Up Kubeflow Cluster
4:27 - Explanation of Kubeflow's Features and Tools
5:08 - Deep Dive into Llama 2 and Kerve for Model Inference
6:01 - Application of LLMs and Savings on ChatGPT Costs
6:59 - Detailed Coding Session and API Walkthrough
18:14 - Insights on Model Deployment and Kserve Usage
22:30 - Showcasing Kubeflow Central Dashboard and Setting Up Services
27:56 - Demonstrating Kubeflow Notebooks and Running Examples
37:03 - Integration with OpenAI SDK and API Discussion
47:00 - Retrieval Augmented Generation (RAG) Demonstration
54:04 - Final Remarks and Open Q&A Session