/DSEF

Data Science Engineering Fundamentals

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Data Science Engineering Fundamentals Program

The Open Source resources in Data Engineering, Cloud Computing, Machine Learning, Data Science and Artificial Intelligence topics, inspired by Data Science Masters.

Table of contents:

Reference Books and Research Papers:

Books:

Docker for Data Science by Joshua Cook

Data Wrangling with Python by Jacqueline Kazil, Katharine Jarmul

Introduction to Machine Learning with Python by Andreas C. Mueller , Sarah Guido

Python Machine Learning (2nd Ed.) Code Repository by Sebastian Raschka, Vahid Mirjalili

The Elements of Statistical Learning T.Hastie, R.Tibshirani, J.Friedman

Natural Language Processing with Python Analyzing Text with the Natural Language Toolkit by Steven Bird, Ewan Klein, and Edward Loper http://www.nltk.org/book/ http://www.nltk.org/book_1ed/

Deep Learning Book by Ian Goodfellow, Yoshua Bengio, Aaron Courville https://www.deeplearningbook.org/

Deep Learning with Python by François Chollet https://www.manning.com/books/deep-learning-with-python

Practical DevOps by Joakim Verona

Effective DevOps with AWS: Ship faster, scale better, and deliver incredible productivity Paperback – July 31, 2017 by Nathaniel Felsen

Papers:

Paper by Tomas Mikolov Google http://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf

Resources https://medium.com/ https://towardsdatascience.com/machine-learning/home https://www.datasciencecentral.com/ https://www.kdnuggets.com/

LearningCourses: https://www.coursera.org/ https://eu.udacity.com/ https://www.datacamp.com/ https://cloudacademy.com https://www.edx.org/ http://udemy.com http://www.deeplearningbook.org/