Technical books

Here a list of some books I have found useful in the areas of machine learning and natural language processing. I put in cyan background those that are focused on NLP.

Albon, Chris (2018) Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning. O'Reilly 978-1-4919-8938-8
Bengfort, Benjamin; Ojeada, Tony, Bilbro, Rebecca (2018) Applied Text Analysis with Python 978-1491963036
Bishop, Christopher (2008) Pattern Recognition and Machine Learning. Springer Verlag 978-0-3873-1073-2
Flach, Peter (2012) Machine Learning: The Art and Science of Algorithms that Make Sense of Data. Cambridge University Press 978-1-107-42222-3
Ganegedara, Thushan (2018) Natural Language Processing with TensorFlow, Packt. 978-1-78847831-1
Géron, Aurélien (2017) Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems. O'Reilly Media 978-1-491-96229-9
Goodfellow Ian; Bengio Yoshua and Courville, Aaron (2016) Deep Learning 978-0-262-03561-3
Ingersoll & alia (2013) Taming Text: How to Find, Organize, and Manipulate It 978-1933988382
Koehn, Philipp (2010) Statistical Machine Translation 978-0521874151
Lunde (2019) CJKV Information Processing: Chinese, Japanese, Korean & Vietnamese Computing 978-0596514471
Manning & Schütze (1999) Foundations of Statistical Natural Language Processing 978-0262133609
Raschka, Sebastian (2015) Python Machine Learning, Packt Open Source 978-1-78355-513-0
Witten, Ian H.; Eibe Frank (2011) Data Mining: Practical machine learning tools and techniques Morgan Kaufmann 978-0-12-374856-0
Various Coli MIT Periodical
Andrés Domínguez Burgos, 2020 ©