Learn how to automate LLMs with feature engineering and streamline ML pipelines with Hopsworks, making data transformation and deployment more efficient and scalable. In our latest Show, Don't Tell, our Software Engineer Aleksey Veresov and Head of Strategy Lex Avstreikh walks you through:
- How to automate feature engineering for LLMs to improve accuracy and efficiency
- How to streamline ML pipelines to reduce complexity and manual intervention
- How Hopsworks enables scalable, real-time data transformation and deployment
Watch on Demand: Get Your DeepSeek Models Running with Hopsworks π
If you missed our webinar we did on DeepSeek, we've got you covered! You can now watch the full video at your leisure. We uncover how you can get DeepSeek models running in an on-premises or cloud-based Kubernetes cluster in minutes.
Recommended Content π
π οΈ Building Feature Pipelines with Apache Flink
Find out how to use Flink to compute real-time features and make them available to online models within seconds using Hopsworks.
π From MLOps to ML System with FTI Pipelines
Learn about the three pipelines for building ML systems; Feature, Training and Inference pipelines.
π₯ Batch and Real-Time Machine Learning System
In this video, explore the machine learning pipeline framework FTI and how it's a mind map for ML Systems, both batch and real-time.