From Concept to Production - Template for the Entire Machine Learning Journey
Offered By: Toronto Machine Learning Series (TMLS) via YouTube
Course Description
Overview
Embark on a comprehensive 3-hour workshop that guides you through the entire machine learning journey, from concept to production. Learn how to create an open-source template in Python for building and deploying ML components. Begin with an example use case, constructing essential elements such as data preparation, model hyper-training, model training, deployment, and online/batch prediction. Gain hands-on experience unit testing these components in a Python notebook. Advance to deploying the components in a Kubeflow pipeline with orchestration for training and prediction, resulting in a production-ready ML pipeline. Implement the tutorial on Google Cloud Platform with Vertex AI, working with XGBoost and TensorFlow models. By the end of this workshop, acquire practical skills to develop and deploy machine learning solutions from initial concept to final production pipeline.
Syllabus
From Concept to Production Template for the Entire ML Journey
Taught by
Toronto Machine Learning Series (TMLS)
Related Courses
How Google does Machine LearningGoogle Cloud via Coursera Google Cloud Big Data and Machine Learning Fundamentals en Español
Google Cloud via Coursera Google Cloud Big Data and Machine Learning Fundamentals 日本語版
Google Cloud via Coursera How Google does Machine Learning 日本語版
Google Cloud via Coursera How Google does Machine Learning em Português Brasileiro
Google Cloud via Coursera