-
The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Trevor Hastie, Robert Tibshirani, Jerome Friedman (2009) https://web.stanford.edu/~hastie/ElemStatLearn/
-
An Introduction to Statistical Learning with Applications in R Gareth James, Daniela Witten… in Springer Texts in Statistics (2013) https://link.springer.com/book/10.1007/978-1-4614-7138-7
-
Mastering Machine Learning with Python in Six Steps: A Practical Implementation Guide to Predictive Data Analytics Using Python Manohar Swamynathan (2017) https://link.springer.com/book/10.1007/978-1-4842-2866-1
-
Python Data Analytics - Data Analysis and Science Using Pandas, matplotlib, and the Python Programming Language Fabio Nelli (2015) https://link.springer.com/book/10.1007/978-1-4842-0958-5
-
Python for Probability, Statistics, and Machine Learning José Unpingco (2016) https://link.springer.com/book/10.1007/978-3-319-30717-6
-
Introduction to Data Science - A Python Approach to Concepts, Techniques and Applications Laura Igual, Santi Seguí in Undergraduate Topics in Computer Science (2017) https://link.springer.com/book/10.1007/978-3-319-50017-1
-
Python Recipes Handbook - A Problem-Solution Approach Joey Bernard (2016) https://link.springer.com/book/10.1007/978-1-4842-0241-8
-
Beginning Python Visualization - Crafting Visual Transformation Scripts Shai Vaingast (2014) https://link.springer.com/book/10.1007/978-1-4842-0052-0
-
Python Algorithms - Mastering Basic Algorithms in the Python Language Magnus Lie Hetland (2014) https://link.springer.com/book/10.1007/978-1-4842-0055-1
-
Text Analytics with Python - A Practical Real-World Approach to Gaining Actionable Insights from your Data Dipanjan Sarkar (2016) https://link.springer.com/book/10.1007/978-1-4842-2388-8
-
An Introduction to Statistics with Python With Applications in the Life Sciences Thomas Haslwanter in Statistics and Computing (2016) https://link.springer.com/book/10.1007/978-3-319-28316-6
-
A Primer on Scientific Programming with Python Hans Petter Langtangen in Texts in Computational Science and Engineering (2014) https://link.springer.com/book/10.1007/978-3-642-54959-5
- _Deep Learning_Yoshua Bengio, Ian Goodfellow and Aaron Courville (2015) http://www.iro.umontreal.ca/~bengioy/dlbook/
- Neural Networks and Deep Learning Michael Nielsen (Dec 2014) [http://neuralnetworksanddeeplearning.com/]http://neuralnetworksanddeeplearning.com/)
- Deep Learning Microsoft Research (2013) http://research.microsoft.com/pubs/209355/DeepLearning-NowPublishing-Vol7-SIG-039.pdf
- Deep Learning Tutorial LISA lab, University of Montreal (2015) http://deeplearning.net/tutorial/deeplearning.pdf
- neuraltalk Andrej Karpathy : numpy-based RNN/LSTM implementation https://github.com/karpathy/neuraltalk
- An introduction to genetic algorithms https://svn-d1.mpi-inf.mpg.de/AG1/MultiCoreLab/papers/ebook-fuzzy-mitchell-99.pdf
- Artificial Intelligence: A Modern Approach http://aima.cs.berkeley.edu/
- Deep Learning in Neural Networks: An Overview http://arxiv.org/pdf/1404.7828v4.pdf