Continuous Delivery for Machine Learning Applications with Open Source Tools

Explore a comprehensive conference talk on implementing continuous delivery for machine learning applications using open-source tools. Learn how to bring intelligent applications into production environments, scale them effectively, maintain high quality, and continuously improve them. Discover the process of developing an HR services chatbot using rasa.ai, TensorFlow, and Keras, and how to organize development with mixed teams of product owners, data scientists, dialog designers, data engineers, and machine learning developers. Gain insights into using pipelines, version control mechanisms for various artifacts, quality gates, and continuous delivery orchestration to automate the process of developing and improving chatbots. Understand how to move models from data scientists' notebooks into production, enabling continuous improvement and experimentation with live users. Acquire knowledge on applying Continuous Delivery for Machine Learning and its significant benefits. Conclude with an outlook on future developments in software engineering practices for machine learning applications.

Continuous Delivery for Machine Learning Applications with Open Source Tools