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MLOps World: Machine Learning in Production

Productionize with Kubeflow Orchestration and Feast in GCP - Workshop

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Develop a machine learning framework using Kubeflow, Feast, and Kafka in GCP. Learn to manage data features, serve endpoints, and monitor model performance with Grafana for real-time and batch predictions.
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1 Lesons
1 hour 48 minutes
On-Demand
Free-Video
Prodramp

An AI Engineer Technical Guide to Feature Store with FEAST

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Comprehensive guide to FEAST feature store for AI engineers, covering installation, setup, data handling, and integration with machine learning models. Includes hands-on examples and architecture review.
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23 Lesons
48 minutes
On-Demand
Free-Video
Databricks

Scaling Data and ML with Apache Spark and Feast - Feature Engineering for Production

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Explore scaling data and ML with Apache Spark and Feast, focusing on feature engineering challenges and solutions for big data-driven machine learning in production environments.
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23 Lesons
38 minutes
On-Demand
Free-Video
Linux Foundation

Self-serve Feature Engineering Platform Using Flyte and Feast

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Explore a self-serve feature engineering platform leveraging Flyte and Feast technologies, enhancing data science workflows and machine learning model development.
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1 Lesons
51 minutes
On-Demand
Free-Video
Linux Foundation

Integrating Feast Online Feature Store with KFServing

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Explore integrating Feast online feature store with KFServing for efficient machine learning model serving, featuring insights from IBM experts on deployment and implementation.
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17 Lesons
36 minutes
On-Demand
Free-Video
Linux Foundation

Integrating High Performance Feature Stores with KServe Model Serving

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Explore high-performance feature stores integration with KServe for efficient ML model serving, focusing on Feast concepts, KServe challenges, and scalable architectures.
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16 Lesons
29 minutes
On-Demand
Free-Video
Linux Foundation

The Challenges of Deploying Real-time AI for Finance and How Open Source Can Help

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Exploring challenges in deploying real-time AI for finance and how open-source solutions like feature stores can address them. Includes case studies and resources for implementing MLOps in fintech.
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1 Lesons
43 minutes
On-Demand
Free-Video
CNCF [Cloud Native Computing Foundation]

Building a Cloud Native Feature Store with Feast on Kubeflow

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Explore how Feast, an open-source feature store, solves key challenges in machine learning feature engineering, from data processing to production deployment, within a cloud-native Kubeflow environment.
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1 Lesons
32 minutes
On-Demand
Free-Video
Toronto Machine Learning Series (TMLS)

Building a Fraud Detection Model with Feature Stores - Includes Shopify Case Study

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Develop a real-time fraud detection system using ML data pipeline tools. Learn to build, deploy, and serve data pipelines with Feast and Tecton. Explore architectural patterns and model stages.
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1 Lesons
1 hour 12 minutes
On-Demand
Free-Video
MLOps.community

AI Innovations: The Power of Feature Platforms - MLOps Mini Summit

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Explore feature platforms for production AI, including Tecton's unified approach, Cleo's custom solution, and DIY strategies for building scalable, flexible ML infrastructures.
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12 Lesons
1 hour 5 minutes
On-Demand
Free-Video