Getting Machine Learning Models into Use

Explore the critical steps in deploying machine learning models for biological data analysis in this 35-minute talk. Learn about the entire value chain, from data gathering and preprocessing to model training and deployment. Discover practical strategies for making bioinformatics projects accessible to end-users, with insights from Jeppe Hallgren, author of the Open Protein machine learning framework. Gain valuable knowledge on scalability, cross-platform compatibility, and tailoring tools for diverse scientific audiences. Address key challenges in data security, protection of sensitive biological information, and long-term maintainability. Dive into topics such as creating web servers, zero-knowledge proofs, secure enclaves, and utilizing tools like Google Colab, pandas, and scikit-learn to enhance your machine learning deployment skills.

Introduction
How do we share results
Creating web servers
Zero knowledge
Challenges
Secure Enclave
Google CoOp
pandas
sklearn