Principles of Database Management:
The Practical Guide to Storing, Managing and Analyzing Big and Small Data
Coming 2018. This book covers the principles of database management. It starts by defining databases and the various steps of database design. A next part zooms into different types of database systems: pre-relational, relational, object oriented, XML and no-SQL databases. Subsequent chapters discuss transaction management and physical data storage aspects. Also data access and data integration in an x-tier environment are extensively covered. The book concludes by discussing data warehousing, big data and analytics. Throughout the book, we will include various examples and case studies to illustrate and clarify the concepts discussed. Every chapter will conclude with a set of self-study questions such that the book can be easily used as a textbook by colleague instructors. We will also extensively report on both our research and industry experience on the topic to further illustrate the practical impact of the concepts discussed.
→ Read more information and be notified when the book releases over at www.pdbmbook.com!
→ Access YouTube courses.
Credit Risk Analytics: The R Companion
Credit risk analytics in R will enable you to build credit risk models from start to finish. Accessing real credit data via the accompanying website www.creditriskanalytics.net, you will master a wide range of applications, including building your own PD, LGD and EAD models as well as mastering industry challenges such as reject inference, low default portfolio risk modeling, model validation and stress testing. This book has been written as a companion to Baesens, B., Roesch, D. and Scheule, H., 2016. Credit Risk Analytics: Measurement Techniques, Applications, and Examples in SAS. John Wiley & Sons.
Practical Web Scraping for Data Science:
Best Practices and Examples with Python
Get Started with Web Scraping using Python!
Congratulations! By picking up this book, you’ve set the first steps into the exciting world of web scraping. For those who are not familiar with programming or the deeper workings of the web, web scraping often looks like a black art: the ability to write a program that sets off on its own to explore the Internet and collect data is seen as a magical and exciting ability to possess. In this book, we set out to provide a concise and modern guide to web scraping, using Python as our programming language, without glossing over important details or best practices. In addition, this book is written with a data science audience in mind. We’re data scientists ourselves, and have very often found web scraping to be a powerful tool to have in your arsenal, as many data science projects start with the first step of obtaining an appropriate data set, so why not utilize the treasure trove of information the web provides.
→ Read more information and get example source code over at www.webscrapingfordatascience.com!
Web Scraping for Data Science with Python
Authors: Seppe vanden Broucke, Bart Baesens
Paperback: 256 pages
Publisher: CreateSpace Independent Publishing Platform (November 30, 2017)
Get it on: Re-released with Apress (see above)
Profit Driven Business Analytics:
A Practitioner’s Guide to Transforming Big Data into Added Value
Maximize profit and optimize decisions with advanced business analytics
Profit-Driven Business Analytics provides actionable guidance on optimizing the use of data to add value and drive better business. Combining theoretical and technical insights into daily operations and long-term strategy, this book acts as a development manual for practitioners seeking to conceive, develop, and manage advanced analytical models.
Credit Risk Analytics:
Measurement Techniques, Applications, and Examples in SAS
The long-awaited, comprehensive guide to practical credit risk modeling
Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management. Combining theory with practice, this book walks you through the fundamentals of credit risk management and shows you how to implement these concepts using the SAS credit risk management program, with helpful code provided.
→ Obtain the data sets used in the book here.
Using Supervised, Unsupervised and Social Network Learning Techniques
Detect fraud before damage cascades
Fraud detection is more valuable the sooner it is made, because further losses are prevented, potential recoveries are higher, and security issues can be addressed more rapidly, as such avoiding cascading damage to an organization. Detecting fraud in an early stage however is harder than detecting it in an evolved stage, and requires specific techniques discussed in this book.
→ Read a sample chapter for free.
Beginning Java Programming:
The Object-Oriented Approach
A comprehensive Java guide, with samples, exercises, case studies, and step-by-step instructions
Beginning Java Programming: The Object Oriented Approach is a straightforward resource for getting started with one of the world’s most enduringly popular programming languages. Based on classes taught by the authors, the book starts with the basics and gradually builds into more advanced concepts. The approach utilizes an integrated development environment that allows readers to immediately apply what they learn, and includes step-by-step instruction with plenty of sample programs.
→ Get started right away by watching our lecture videos and presentations on “Basic Java Programming”.
Analytics in a Big Data World:
The Essential Guide to Data Science and its Applications
The guide to targeting and leveraging business opportunities using big data & analytics
By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior.Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities.
→ Read the first chapter for free.
Credit Risk Management:
Basic Concepts: Financial Risk Components, Rating Analysis, Models, Economic and Regulatory Capital
Get an overview of everything that should be considered when undertaking credit risk management
Credit Risk Management: Basic Concepts is the first book of a series of three with the objective of providing an overview of all aspects, steps, and issues that should be considered when undertaking credit risk management, including the Basel II Capital Accord, which all major banks must comply with in 2008.