Each section in the book is independent and covers a specific algorithm, design method, application field, or related subject. The algorithms are explained and created in a way that is easily understandable for someone with basic programming knowledge.
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Artificial Intelligence
- Raschka, S. (2024). Build a large language model (from scratch). Simon and Schuster.
- Rothman, D. (2024). Transformers for Natural Language Processing and Computer Vision: Explore Generative AI and Large Language Models with Hugging Face, ChatGPT, GPT-4V, and DALL-E 3. Packt Publishing Ltd.
- Goodfellow, I. (2016). Deep Learning-Adaptive Computation and Machine Learning.
- Hart, P. E., Stork, D. G., & Duda, R. O. (2001). Pattern classification. Hoboken: Wiley.
CUDA
- Storti, D., & Yurtoglu, M. (2015). CUDA for engineers: An introduction to high-performance parallel computing. Addison-Wesley Professional.
- Sanders, J., & Kandrot, E. (2010). CUDA by example: An introduction to general-purpose GPU programming. Addison-Wesley Professional.
fMRI
- Poldrack, R. A., Mumford, J. A., & Nichols, T. E. (2024). Handbook of functional MRI data analysis. Cambridge University Press.
- Ashby, F. G. (2019). Statistical analysis of fMRI data. MIT Press.
Linear Algebra
- Singh, K. (2013). Linear algebra: Step by step. OUP Oxford.
- Strang, G. (2012). Linear algebra and its applications.
Medical Imaging
- Maier, A., Steidl, S., Christlein, V., & Hornegger, J. (Eds.). (2018). Medical imaging systems: An introductory guide.
- Gonzalez, R. C., & Woods, R. E. (2018). Digital image processing (Fourth, global edition). Pearson Education.
- McRobbie, D. W., Moore, E. A., Graves, M. J., & Prince, M. R. (2017). MRI from Picture to Proton. Cambridge University Press.
Python
- Gorelick, M., & Ozsvald, I. (2025). High Performance Python: Practical Performant Programming for Humans. O'Reilly Media, Inc.
- Matthes, E. (2023). Python crash course: A hands-on, project-based introduction to programming. No Starch Press.
- VanderPlas, J. (2016). Python data science handbook: Essential tools for working with data. O'Reilly Media, Inc.
Statistics
- Field, A. (2022). An adventure in statistics: The reality enigma.
- Spiegelhalter, D. (2019). The art of statistics: Learning from data. Penguin UK.
- Wheelan, C. (2013). Naked statistics: Stripping the dread from the data. WW Norton & Company.
- Gubner, J. A. (2010). Probability and random processes for electrical and computer engineers (3. printing). Univ. Press.