An Exploration of Python Libraries in Machine Learning Models for Data Science

Author:

Sundaram Jawahar1ORCID,Gowri K.2,Devaraju S.3ORCID,Gokuldev S.4ORCID,Jayaprakash Sujith5ORCID,Anandaram Harishchander6ORCID,Manivasagan C.7,Thenmozhi M.8ORCID

Affiliation:

1. CHRIST University (Deemed), India

2. Sri Ramakrishna College of Arts and Science, India

3. VIT Bhopal University, India

4. Rathinam College of Arts and Science, India

5. BlueCrest University College, Ghana

6. Amrita Vishwa Vidyapeetham, India

7. Rathnavel Subramaniam College of Arts and Science, India

8. Sri Eshwar College of Engineering, India

Abstract

Python libraries are used in this chapter to create data science models. Data science is the construction of models that can predict and act on data, which is a subset of machine learning. Data science is an essential component of a number of fields because of the exponential growth of data. Python is a popular programming language for implementing machine learning models. The chapter discusses machine learning's role in data science, Python's role in this field, as well as how Python can be utilized. A breast cancer dataset is used as a data source for building machine learning models using Python libraries. Pandas, numpy, matplotlib, seaborn, scikit-learn, and tensorflow are some Python libraries discussed in this chapter, in addition to data preprocessing methods. A number of machine learning models for breast cancer treatment are discussed using this dataset and Python libraries. A discussion of machine learning's future in data science is provided at the conclusion of the chapter. Python libraries for machine learning are very useful for data scientists and researchers in general.

Publisher

IGI Global

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