From Concept to Production: Building a Production-Ready ML Pipeline - Part 2
Offered By: MLOps World: Machine Learning in Production via YouTube
Course Description
Overview
Dive into a comprehensive 3-hour and 28-minute workshop session focused on transforming machine learning concepts into production-ready solutions. Learn from Google's AI leaders as they guide you through an open-source Python template covering the entire ML journey. Explore hands-on tutorials for building ML components, including data preparation, model hyper-training, deployment, and prediction. Discover how to deploy these components in a Kubeflow pipeline with orchestration for training and prediction. Gain practical experience in creating production-ready ML pipelines on Google Cloud Platform, working with models such as XGBoost and TensorFlow. By the end of this workshop, acquire the skills to build and deploy end-to-end ML pipelines, bridging the gap between concept and production in the field of machine learning.
Syllabus
Workshop Sessions: Part 2 From Concept to Production - Template for the Entire ML Journey
Taught by
MLOps World: Machine Learning in Production
Related Courses
How Google does Machine Learning en EspaƱolGoogle Cloud via Coursera Creating Custom Callbacks in Keras
Coursera Project Network via Coursera Automatic Machine Learning with H2O AutoML and Python
Coursera Project Network via Coursera AI in Healthcare Capstone
Stanford University via Coursera AutoML con Pycaret y TPOT
Coursera Project Network via Coursera