Creative Commons

https://editorialia.com/wp-content/uploads/2020/02/matlabgrow.png

MATLAB® Notes for Professionals book

This MATLAB® Notes for Professionals book is compiled from Stack Overflow Documentation. (182 pages, published on May 2018)

https://editorialia.com/wp-content/uploads/2020/06/a-whirlwind-tour-of-python.jpg

A Whirlwind Tour of Python

A Whirlwind Tour of Python is a fast-paced introduction to essential features of the Python language, aimed at researchers and developers who are already familiar with programming in another language. The material is particularly designed for those who wish to use Python for data science and/or scientific programming, and in this capacity serves as an introduction to my longer book, The Python Data Science Handbook.

https://editorialia.com/wp-content/uploads/2020/06/r-for-data-science.jpg

R for Data Science

This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science.

https://editorialia.com/wp-content/uploads/2020/06/r-notes-for-professionals-book.jpg

R Notes for Professionals book

This R Notes for Professionals book is compiled from Stack Overflow Documentation. (475 pages, published on May 2018)

https://editorialia.com/wp-content/uploads/2020/06/select-star-sql-2.jpg

Select Star SQL

This is an interactive book which aims to be the best place on the internet for learning SQL. It is free of charge, free of ads and doesn’t require registration or downloads. It helps you learn by running queries against a real-world dataset to complete projects of consequence. It is not a mere reference page — it conveys a mental model for writing SQL.

https://editorialia.com/wp-content/uploads/2020/06/python-notes-for-professionals-book.jpg

Python® Notes for Professionals book

This Python® Notes for Professionals book is compiled from Stack Overflow Documentation. (816 pages, published on June 2018)

https://editorialia.com/wp-content/uploads/2020/02/a-quantum-engineers-guide-to-superconducting-qubits-1.jpg

A quantum engineer’s guide to superconducting qubits

Discussed the phenomenalprogress over the last decade in the engineering of superconducting devices, the development of high-fidelitygate operations, and quantum non-demolition measurements with high signal to noise ratio.

https://editorialia.com/wp-content/uploads/2020/06/a-programmers-guide-to-data-mining-ebook-1.jpg

A Programmers Guide to Data Mining ebook

This book is a guide to practical data mining, collective intelligence, and building recommendation systems by Ron Zacharski (Zen Buddhist monk and computational linguist).

https://editorialia.com/wp-content/uploads/2020/02/machine-learning-and-deep-learning-frameworks-and-libraries-for-large-scale-data-mining-a-survey.jpg

Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey

The combined impact of new computing resources and techniques with an increasing avalanche of large datasets, is transforming many research areas and may lead to technological breakthroughs that can be used by billions of people. In the recent years, Machine Learning and especially its subfield Deep Learning have seen impressive advances. Techniques developed within these two fields are now able to analyze and learn from huge amounts of real world examples in a disparate formats. While the number of Machine Learning algorithms is extensive and growing, their implementations through frameworks and libraries is also extensive and growing too.

https://editorialia.com/wp-content/uploads/2020/06/free-and-open-machine-learning-documentation-release-03.jpg

Free and Open Machine Learning Documentation Release 1.0.1

This book is all about applying machine learning solutions for real practical use cases. This means the core focus is on outlining how to use machine learning in a simple way so you can benefit of this powerful technology.
Machine learning is an exciting and powerful technology. The continuous use and growth of machine learning technology opens new opportunities. This great technology should available to use for everyone. This means that everyone should be able to learn, play and create great applications using machine learning technology.