In the preface, we mentioned that this book is designed for readers who are looking for tools in the area of data science. Existing data analysts and data science professionals who wish to improve the efficiency of their data science applications by using the best libraries with multiple languages will find this book quite useful. The platform discussed in detail across various chapters is Anaconda and the computational tools could be Python, R, Julia, or Octave. The beauty of using these programming languages is that they are all open source, as in free to download. In this chapter, we start from the very beginning: a simple introduction. For this book, we assume that readers have some basic knowledge related to several programming languages, such as R and Python. There are many books available, such as Python for Data Analysis by McKinney (2013) and Python for Finance by Yan (2017).
In this chapter, the following topics will be covered:
- Introduction
- Miniconda
- Anaconda Cloud
- Finding help