Data Science, Notebooks, and Kernels
Data science seems like it is at an all-time high in popularity as advances in computing, storage, and data analysis have made new types of applications not just possible, but accessible to people who traditionally wouldn’t call themselves data scientists.
This book aims to help developers expand their existing knowledge and capabilities into the fields of data science, machine learning, artificial intelligence (AI), and data analysis.
In this opening chapter, we’ll cover these broad topics and explore what the field of data science includes, how the various parts of data science relate to each other, and how data science notebooks enable you to perform new tasks in new ways.
This chapter covers the following topics:
- Exploring the field of data science
- Data science notebooks and Project Jupyter
- Extending notebooks with kernels
- Polyglot Notebooks and .NET Interactive
