Bibliografia

Literatura complementar será fornecida durante o curso.

1. V.K. Ayyadevara and Y. Reddy. Modern Computer Vision with Pytorch. Packt, Second ed., 2024.

2. S. Raschka. Build a Large Language Model (From Scratch), Manning, Sep 2024.

3. F. Chollet. Deep Learning with Python. Manning, 3rd edition, 2025.

4. A. Zhang, Z.C. Lipton, M. LI, and A.J. Smola. Dive into Deep Learning: Interactive deep learning book with code, math, and discussions, https://d2l.ai/, 2020.

5. A. Géron. Hands-on Machine Learning with Scikit-Learn, Keras & Tensorflow. O'Reilly, 2nd Ed., 2019.

6. S. Vajjala, B. Majumder, A. Gupta, and H. Surana. Practical Natural Language Processing. O'Reilly, 2020.

7. D. Sarkar. Text Analytics with Python. Apress, 2019.

8. S. Ravichandiran. Getting started with Google BERT. Packt, 2021.

9. K. Koutroumbas and S. Theodoridis. Pattern Recognition. 4th Ed., Academic Press, 2009.

10. R.O. Duda, P.E. Hart, and D.G. Stork. Pattern Classification, 2nd edition, 2001.