You're reading from Data Science Projects with Python - Second Edition

Product typeBook

Published inJul 2021

Reading LevelIntermediate

PublisherPackt

ISBN-139781800564480

Edition2nd Edition

Languages

Python

Concepts

Data Science

Author (1)

Stephen Klosterman

Loading the Case Study Data with Jupyter and pandas

Now it's time to take a first look at the data we will use in our case study. We won't do anything in this section other than ensure that we can load the data into a Jupyter notebook correctly. Examining the data, and understanding the problem you will solve with it, will come later.

The data file is an Excel spreadsheet called default_of_credit_card_clients__courseware_version_1_21_19.xls. We recommend you first open the spreadsheet in Excel or the spreadsheet program of your choice. Note the number of rows and columns. Look at some example values. This will help you know whether or not you have loaded it correctly in the Jupyter notebook.

Note

The dataset can be obtained from the following link: https://packt.link/wensZ. This is a modified version of the original dataset, which has been sourced from the UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School...

The rest of the page is locked

You have been reading a chapter from

Data Science Projects with Python - Second Edition

Published in: Jul 2021Publisher: PacktISBN-13: 9781800564480

Author (1)

Stephen Klosterman

Stephen Klosterman is a Machine Learning Data Scientist with a background in math, environmental science, and ecology. His education includes a Ph.D. in Biology from Harvard University, where he was an assistant teacher of the Data Science course. His professional experience includes work in the environmental, health care, and financial sectors. At work, he likes to research and develop machine learning solutions that create value, and that stakeholders understand. In his spare time, he enjoys running, biking, paddleboarding, and music.
Read more about Stephen Klosterman

Other recommended products

Related to this chapter

Data Science Projects with Python

Data Science Projects with Python will help you build a toolkit for solving data science problems with Python. You will learn how to implement machine learning techniques for deriving insights from data. These skills will help you develop the kind of state-of-the-art predictive models that are used to deliver value to businesses across industries.

BookApr 2019374 pages

Mastering Predictive Analytics with scikit-learn and TensorFlow

In this book, you will find a range of methods to improve the performance of almost any predictive model, from ensemble methods to dimensionality reduction and cross-validation. You will learn the tools to produce advanced predictive models. In addition, you will dive into the exiting field of Deep Learning using TensorFlow.

BookSep 2018154 pages

Machine Learning with scikit-learn Quick Start Guide

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize and evaluate all the important machine learning algorithms that scikit-learn provides.

BookOct 2018172 pages

Hands-On Gradient Boosting with XGBoost and scikit-learn

This practical XGBoost guide will put your Python and scikit-learn knowledge to work by showing you how to build powerful, fine-tuned XGBoost models with impressive speed and accuracy. This book will help you to apply XGBoost’s alternative base learners, use unique transformers for model deployment, discover tips from Kaggle masters, and much more!

BookOct 2020310 pages

Hands-On Predictive Analytics with Python

This book will teach you all the processes you need to build a predictive analytics solution: understanding the problem, preparing datasets, exploring relationships, model building, tuning, evaluation, and deployment. You'll earn to use Python and its data analytics ecosystem to implement the main techniques used in real-world projects.

BookDec 2018330 pages

Data Science for Marketing Analytics

Data Science for Marketing Analytics opens doors to looking at data with a different approach and new tools. Drawing on machine learning and data science concepts, this book broadens the range of tools that you can use to transform the market analysis process.

BookMar 2019420 pages

Hands-On Ensemble Learning with Python

Ensemble learning can provide the necessary methods to improve the accuracy and performance of existing models. In this book, you'll understand how to combine different machine learning algorithms to produce more accurate results from your models.

BookJul 2019298 pages

Applied Deep Learning with Keras

Applied Deep Learning with Keras takes you from a basic knowledge of machine learning and Python to an expert understanding of applying Keras to develop efficient deep learning solutions. This book teaches you new techniques to handle neural networks, and in turn, broadens your options as a data scientist.

BookApr 2019412 pages

The Deep Learning with Keras Workshop

Cut through the noise and get real results with a step-by-step approach to understanding deep learning with Keras programming

BookFeb 2020446 pages

Ensemble Machine Learning Cookbook

This book uses a recipe-based approach to showcase the power of machine learning algorithms to build ensemble models using Python libraries. Through this book, you will be able to pick up the code, understand in depth how it works, execute and implement it efficiently. This will be a desk reference to implement a wide range of tasks and solve the common and uncommon problems in ensemble machine learning domain.

BookJan 2019336 pages

Mastering Machine Learning with scikit-learn

This book examines machine learning models including k-nearest neighbors, logistic regression, naive Bayes, random forests, and support vector machines. You will work through document classification, image recognition, and other example problems.

BookJul 2017254 pages

scikit-learn Cookbook

scikit-learn has evolved as a robust library for machine learning applications in python with support for a wide range of supervised and unsupervised learning algorithms. This edition brings to you the various enhancements to its model implementations, API and bug fixes in the latest major release of scikit-learn to support Python. This book covers easy to follow recipes right from mathematical operations to implementing various supervised, unsupervised and deep learning algorithms with scikit-learn. Get practical hands-on knowledge to implement various models and algorithms like Multi-Layer Perceptrons, time-series split, MAE criterion for regression, criteria for gradient boosting, Classifier, Regressor, and much more.

BookNov 2017374 pages

Personalised recommendations for you

Based on your interests and search pattern

Et al.

Ever wonder why speech recognition systems don't understand the Scottish accent, or what would happen if an astronaut only ate mac 'n' cheese, or other spurious reflections you'd have at a bar? We did, then collated those deliberations into absurd research articles with fake figures and methodologies inspired by even more fictionally absurd studies.

BookAug 2023230 pages5

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages4

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages5

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages1

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

BookDec 2023360 pages5

Mastering Tableau 2023

This book is a comprehensive resource to mastering your Tableau skills and becoming a BI expert. As you progress, you will learn how to build advanced dashboards and improve your storytelling to derive key business insight, as well as make you well-versed with advanced functionalities of Tableau in the business intelligence domain.

BookAug 2023684 pages

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

BookSep 2023258 pages5

Building AI Applications with ChatGPT APIs

This guide covers all ChatGPT API features for effortless creation of robust AI powered apps. With its help, you’ll be able to leverage ChatGPT’s cutting-edge NLP models to take your app development skills to the next level. You’ll also work on ten exciting projects that will give you the practical know-how that you can apply to your existing applications.

BookSep 2023258 pages2

Data Engineering with AWS

Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.

BookOct 2023636 pages5

Modern Data Architecture on AWS

Every organization wants an agile, performant, and cost-effective data platform that meets all their current and future business needs. Purpose-built AWS analytics services and their features play a big part in building such a modern data platform. This book brings to you all the design and architectural patterns that’ll help you achieve this goal.

BookAug 2023420 pages5

Practical Guide to Applied Conformal Prediction in Python

Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.

BookDec 2023240 pages

TinyML Cookbook

With over 70 project-based recipes, the TinyML Cookbook is a practical guide that will help you to get the most out of your microcontrollers. It provides a comprehensive understanding of the theoretical foundations while giving you hands-on experience training ML models for deployment on Arduino Nano 33 BLE Sense, Raspberry Pi Pico, and SparkFun RedBoard Artemis Nano microcontrollers.

BookNov 2023664 pages

You're reading from Data Science Projects with Python - Second Edition

Loading the Case Study Data with Jupyter and pandas

Unlock this book and the full library FREE for 7 days

Author (1)

Data Science Projects with Python

Mastering Predictive Analytics with scikit-learn and TensorFlow

Machine Learning with scikit-learn Quick Start Guide

Hands-On Gradient Boosting with XGBoost and scikit-learn

Hands-On Predictive Analytics with Python

Data Science for Marketing Analytics

Data Science for Marketing Analytics opens doors to looking at data with a different approach and new tools. Drawing on machine learning and data science concepts, this book broadens the range of tools that you can use to transform the market analysis process.

Hands-On Ensemble Learning with Python

Ensemble learning can provide the necessary methods to improve the accuracy and performance of existing models. In this book, you'll understand how to combine different machine learning algorithms to produce more accurate results from your models.

Applied Deep Learning with Keras

The Deep Learning with Keras Workshop

Cut through the noise and get real results with a step-by-step approach to understanding deep learning with Keras programming

Ensemble Machine Learning Cookbook

Mastering Machine Learning with scikit-learn

This book examines machine learning models including k-nearest neighbors, logistic regression, naive Bayes, random forests, and support vector machines. You will work through document classification, image recognition, and other example problems.

scikit-learn Cookbook

Et al.

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Generative AI with LangChain

This book is a comprehensive introduction to LLMs and LangChain, demystifying the basic mechanics of LangChain, its functionalities, and the myriad of applications it can be integrated into.

Mastering Tableau 2023

Building AI Applications with ChatGPT APIs

Building AI Applications with ChatGPT APIs

Data Engineering with AWS

Embark on a journey to master data engineering pipelines on AWS! Our book offers a hands-on experience of AWS services for ingesting, transforming, and consuming data. Whether you're an absolute beginner or someone with basic data engineering experience, this guide is an indispensable resource.

Modern Data Architecture on AWS

Practical Guide to Applied Conformal Prediction in Python

Discover the power of Conformal Prediction with the "Practical Guide to Applied Conformal Prediction in Python." Master the latest techniques to quantify uncertainty in machine learning and computer vision models, and seamlessly apply them to your industry applications.

TinyML Cookbook