Sumário (provisório)¶
Capítulo 1: Visão geral do livro (Este capítulo)
Capítulo 2: Contexto
Capítulo 3: Primeiros passos
Capítulo 4: Métricas de desempenho
Capítulo 5: Seleção de modelo
Capítulo 6: Aprendizagem desbalanceada
Capítulo 7: Aprendizagem profunda
Capítulo 8: Interpretabilidade*
(*): Ainda não publicado.
Público-alvo¶
Estudantes ou profissionais, interessados no problema específico de detecção de fraude em cartões de crédito de um ponto de vista prático
De forma mais geral, praticantes de dados e cientistas de dados que lidam com problemas de aprendizado de máquina que envolvem dados sequenciais tabulares e/ou problemas de classificação desbalanceada
Pré-requisitos¶
Familiaridade com a linguagem Python e a biblioteca scikit-learn
Familiaridade com processos de ciência de dados e aprendizado de máquina
Livros recomendados:
Gianluca Bontempi. Statistical foundations of machine learning, 2nd Edition. Université Libre de Bruxelles, 2021 Bontempi (2021)
Andreas C Müller and Sarah Guido. Introduction to machine learning with Python: a guide for data scientists. O’Reilly Media, Inc., 2016 Müller & Guido (2016)
Wes McKinney. Python for data analysis: Data wrangling with Pandas, NumPy, and IPython - 2nd Edition. O’Reilly Media, Inc., 2017 McKinney (2017)
Machine Learning Group - Publicações recomendadas:
Wissam Siblini, Guillaume Coter, Rémy Fabry, Liyun He-Guelton, Frédéric Oblé, Bertrand Lebichot, Yann-Aël Le Borgne, and Gianluca Bontempi. Transfer learning for credit card fraud detection: A journey from research to production. In Proceedings of the Data Science and Advanced Analytics (DSAA 2021), 2021 Siblini et al. (2021)
Bertrand Lebichot, Théo Verhelst, Yann-Aël Le Borgne, Liyun He-Guelton, Frédéric Oblé, and Gianluca Bontempi. Transfer learning strategies for credit card fraud detection. IEEE access, 9:114754–114766, 2021 Lebichot et al. (2021)
Bertrand Lebichot, Gian Marco Paldino, W Siblini, L He-Guelton, F Oblé, and G Bontempi. Incremental learning strategies for credit cards fraud detection. International Journal of Data Science and Analytics, pages 1–10, 2021 Lebichot et al. (2021)
Bertrand Lebichot, Yann-Aël Le Borgne, Liyun He-Guelton, Frédéric Oblé, and Gianluca Bontempi. Deep-learning domain adaptation techniques for credit cards fraud detection. In INNS Big Data and Deep Learning conference, 78–88. Springer, 2019 Lebichot et al. (2019)
Fabrizio Carcillo, Yann-Aël Le Borgne, Olivier Caelen, Yacine Kessaci, Frédéric Oblé, and Gianluca Bontempi. Combining unsupervised and supervised learning in credit card fraud detection. Information Sciences, 2019 Carcillo et al. (2019)
Fabrizio Carcillo, Andrea Dal Pozzolo, Yann-Aël Le Borgne, Olivier Caelen, Yannis Mazzer, and Gianluca Bontempi. Scarff: a scalable framework for streaming credit card fraud detection with spark. Information fusion, 41:182–194, 2018 Carcillo et al. (2018)
Fabrizio Carcillo, Yann-Aël Le Borgne, Olivier Caelen, and Gianluca Bontempi. Streaming active learning strategies for real-life credit card fraud detection: assessment and visualization. International Journal of Data Science and Analytics, 5(4):285–300, 2018 Carcillo et al. (2018)
Fabrizio Carcillo. Beyond Supervised Learning in Credit Card Fraud Detection: A Dive into Semi-supervised and Distributed Learning. Université libre de Bruxelles, 2018 Carcillo (2018)
Andrea Dal Pozzolo, Giacomo Boracchi, Olivier Caelen, Cesare Alippi, and Gianluca Bontempi. Credit card fraud detection: a realistic modeling and a novel learning strategy. IEEE transactions on neural networks and learning systems, 29(8):3784–3797, 2017 Dal Pozzolo et al. (2017)
Andrea Dal Pozzolo. Adaptive machine learning for credit card fraud detection. Université libre de Bruxelles, 2015 Dal Pozzolo (2015)
Andrea Dal Pozzolo, Olivier Caelen, Yann-Ael Le Borgne, Serge Waterschoot, and Gianluca Bontempi. Learned lessons in credit card fraud detection from a practitioner perspective. Expert systems with applications, 41(10):4915–4928, 2014 Dal Pozzolo et al. (2014)
- Bontempi, G. (2021). Statistical foundations of machine learning, 2nd edition. Université Libre de Bruxelles.
- Müller, A. C., & Guido, S. (2016). Introduction to machine learning with Python: a guide for data scientists. O’Reilly Media, Inc.
- McKinney, W. (2017). Python for data analysis: Data wrangling with Pandas, NumPy, and IPython - 2nd Edition. O’Reilly Media, Inc.
- Siblini, W., Coter, G., Fabry, R., He-Guelton, L., Oblé, F., Lebichot, B., Borgne, Y.-A. L., & Bontempi, G. (2021). Transfer Learning for Credit Card Fraud Detection: A Journey from Research to Production. Proceedings of Data Science and Advanced Analytics (DSAA 2021). https://arxiv.org/abs/2107.09323
- Lebichot, B., Verhelst, T., Le Borgne, Y.-A., He-Guelton, L., Oblé, F., & Bontempi, G. (2021). Transfer Learning Strategies for Credit Card Fraud Detection. IEEE Access, 9, 114754–114766.
- Lebichot, B., Paldino, G. M., Siblini, W., He-Guelton, L., Oblé, F., & Bontempi, G. (2021). Incremental learning strategies for credit cards fraud detection. International Journal of Data Science and Analytics, 1–10.
- Lebichot, B., Le Borgne, Y.-A., He-Guelton, L., Oblé, F., & Bontempi, G. (2019). Deep-learning domain adaptation techniques for credit cards fraud detection. INNS Big Data and Deep Learning Conference, 78–88.
- Carcillo, F., Le Borgne, Y.-A., Caelen, O., Kessaci, Y., Oblé, F., & Bontempi, G. (2019). Combining unsupervised and supervised learning in credit card fraud detection. Information Sciences.
- Carcillo, F., Dal Pozzolo, A., Le Borgne, Y.-A., Caelen, O., Mazzer, Y., & Bontempi, G. (2018). Scarff: a scalable framework for streaming credit card fraud detection with spark. Information Fusion, 41, 182–194.
- Carcillo, F., Le Borgne, Y.-A., Caelen, O., & Bontempi, G. (2018). Streaming active learning strategies for real-life credit card fraud detection: assessment and visualization. International Journal of Data Science and Analytics, 5(4), 285–300.
- Carcillo, F. (2018). Beyond Supervised Learning in Credit Card Fraud Detection: A Dive into Semi-supervised and Distributed Learning. Université libre de Bruxelles.
- Dal Pozzolo, A., Boracchi, G., Caelen, O., Alippi, C., & Bontempi, G. (2017). Credit card fraud detection: a realistic modeling and a novel learning strategy. IEEE Transactions on Neural Networks and Learning Systems, 29(8), 3784–3797.
- Dal Pozzolo, A. (2015). Adaptive machine learning for credit card fraud detection. Université libre de Bruxelles.
- Dal Pozzolo, A., Caelen, O., Le Borgne, Y.-A., Waterschoot, S., & Bontempi, G. (2014). Learned lessons in credit card fraud detection from a practitioner perspective. Expert Systems with Applications, 41(10), 4915–4928.