Data Science Process

Abstract

With lucrative and millions of job offerings in data science, there are many who aspire to be a data scientist. With the proper learning path, it is possible for most of you to become a data scientist, irrespective of your college education. This chapter starts with the data science process and sets the path for your goal of becoming a data scientist. The chapter gives you a perfect overview of the data science process as followed by a modern data scientist. It discusses both the traditional and modern approaches to model building. The main challenge that today's data scientists face is how to handle enormous image, text, and high-frequency datasets. You will get an overview of the various stages of model building, including algorithm selection, AutoML, and hyper-parameter tuning. The chapter introduces you to ANN/DNN and transfer learning. This chapter, by providing the bird’s eye view of the entire data science process, sets the stage for the rest of the book. It is important that you read this chapter before proceeding with the rest. Most of the other chapters focus on an individual algorithm, technique, or the technology.