13: Data Science in practice
Abstract
The practice chapter primarily focuses on the practical aspects of Data Science, emphasizing hands-on learning. It offers readers step-by-step tutorials to guide them through the implementation of Data Science techniques using the Python programming language. These tutorials cover a diverse range of topics, including data cleaning, preprocessing, feature engineering, model selection, evaluation, and data visualization. The chapter leverages popular Python libraries such as NumPy, Pandas, Scikit-learn, and Matplotlib to provide practical examples of data preprocessing, feature selection, and the training and evaluation of machine learning models.
Keywords
Python; NumPy; Pandas; Scikit-learn; Matplotlib
Data Science ...
Get Fundamentals of Data Science now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
