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

Getting Machine Learning Models into Use

Chemometrics & Machine Learning in Copenhagen
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