Chapter 7 References and Further Reading

7.1 Books and Papers

• Deep Learning with Python by François Chollet (Creator of Keras). A must-read.
• Kelley et al. (2016). “Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks.” Nature Methods.
• Ji et al. (2021). “DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome.” Bioinformatics.

7.2 Online Courses

• Prof. Andrew Ng’s Deep Learning Specialization on Coursera.
• Fast.ai: Practical Deep Learning for Coders.

7.3 Useful Links

• Keras: https://keras.io/
• KerasHub: https://keras.io/keras_cv/ (for pre-trained computer vision models)
• Hugging Face: https://huggingface.co/ (for Transformers models like DNABERT)
• Bioconductor: https://bioconductor.org/