Table of Contents
- Introducing Machine Learning for Genomics
- Genomics Data Analysis
- Machine Learning Methods for Genomic Applications
- Deep Learning for Genomics
- Introducing Convolutional Neural Networks for Genomics
- Recurrent Neural Networks in Genomics
- Unsupervised Deep Learning with Autoencoders
- GANs for Improving Models in Genomics
- Building and Tuning Deep Learning Models
- Model Interpretability in Genomics
- Model Deployment and Monitoring
- Challenges, Pitfalls, and Best Practices for Deep Learning in Genomics

