Introduction to Data Science in Python
In recent years, Python has gained a lot of popularity in the data science field. Its very efficient and readable syntax makes the language a very good choice for scientific research, while still being suitable for production workloads; it’s very easy to deploy research projects into real applications that will bring value to users. Thanks to this growing interest, a lot of specialized Python libraries have emerged and are now standards in the industry. In this chapter, we’ll introduce the fundamental concepts of machine learning before diving into the Python libraries used daily by data scientists.
In this chapter, we’re going to cover the following main topics:
- Understanding the basic concepts of machine learning
- Creating and manipulating NumPy arrays and pandas datasets
- Training and evaluating machine learning models with scikit-learn
