Book Image

Data Science Projects with Python

By : Stephen Klosterman
Book Image

Data Science Projects with Python

By: Stephen Klosterman

Overview of this book

Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools, by applying them to realistic data problems. You will learn how to use pandas and Matplotlib to critically examine datasets with summary statistics and graphs, and extract the insights you seek to derive. You will build your knowledge as you prepare data using the scikit-learn package and feed it to machine learning algorithms such as regularized logistic regression and random forest. You’ll discover how to tune algorithms to provide the most accurate predictions on new and unseen data. As you progress, you’ll gain insights into the working and output of these algorithms, building your understanding of both the predictive capabilities of the models and why they make these predictions. By then end of this book, you will have the necessary skills to confidently use machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data.
Table of Contents (9 chapters)
Data Science Projects with Python
Preface

Chapter 6. Imputation of Missing Data, Financial Analysis, and Delivery to Client

Note

Learning Objectives

By the end of this chapter, you will be able to:

  • Compare the results of all models built for a case study

  • Replace missing data using a range of imputation strategies

  • Build a multiclass classification model

  • Conduct financial analysis to find the optimal threshold for binary classification

  • Derive financial insight from the model to help the client guide budgeting and operational strategy

  • Deliver the model and make recommendations for usage

Note

This chapter presents a comparison of the results from the various models built for a study, describes the financial insights derived from the final model, and outlines the final steps of the project needed to satisfy the client's requirements.