- Добавил: literator
- Дата: 4-01-2022, 17:33
- Комментариев: 0
Название: Practical Data Science for Information Professionals
Автор: David Stuart
Издательство: Facet Publishing
Год: 2020
Страниц: 201
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
The growing importance of Data Science, and the increasing role of information professionals in the management and use of data, are brought together in Practical Data Science for Information Professionals to provide a practical introduction specifically designed for information professionals. This book is not designed as an introduction to programming; it is an introduction to Data Science, for which programming is an extremely useful skill. As can be seen from the examples throughout the book, quite a lot can be achieved with relatively little programming knowledge by building on the work of others. All that is required is an understanding of a few basic concepts (variables, functions, loops). These are briefly covered in the Appendix, which gives simple examples for R and Python. R and Python are only two of the many hundreds of computer languages available. This book uses Python and R: Python because of its versatility and widespread use, and R because of the statistical packages that have been built for it. R and Python are very powerful, extensive languages with active sets of users, and the web is filled with tutorials for them.
Автор: David Stuart
Издательство: Facet Publishing
Год: 2020
Страниц: 201
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
The growing importance of Data Science, and the increasing role of information professionals in the management and use of data, are brought together in Practical Data Science for Information Professionals to provide a practical introduction specifically designed for information professionals. This book is not designed as an introduction to programming; it is an introduction to Data Science, for which programming is an extremely useful skill. As can be seen from the examples throughout the book, quite a lot can be achieved with relatively little programming knowledge by building on the work of others. All that is required is an understanding of a few basic concepts (variables, functions, loops). These are briefly covered in the Appendix, which gives simple examples for R and Python. R and Python are only two of the many hundreds of computer languages available. This book uses Python and R: Python because of its versatility and widespread use, and R because of the statistical packages that have been built for it. R and Python are very powerful, extensive languages with active sets of users, and the web is filled with tutorials for them.