Part 3 – Operationalizing models
This part will describe operationalizing models, which includes training, tuning, validating, deploying, and monitoring models. In addition, this part will describe model interpretability along with the pitfalls, challenges, and best practices for machine learning and deep learning technologies for genomic applications.
This section comprises the following chapters:
Chapter 9, Building and Tuning Deep Learning Models
Chapter 10, Model Interpretability in Genomics
Chapter 11, Model Deployment and Monitoring
Chapter 12, Challenges, Pitfalls, and Best Practices for Deep Learning in Genomics
