Master the art of predictive modeling with XGBoost and gain hands-on experience in building powerful regression, classification, and time series models using the XGBoost Python APIKey FeaturesGet up and running with this quick-start guide to building a classifier using XGBoostGet an easy-to-follow, in-depth explanation of the XGBoost technical paperLeverage XGBoost for time series forecasting by using moving average, frequency, and window metho...

This Second Edition addresses five common pitfalls that prevent projects from reaching deployment and provides tools and methods to avoid these pitfalls. Current statistics show that 87% of AI and Big Data projects fail by never reaching deployment, making this book an essential resource for data science and AI practitioners, as well as managers. The author illustrates the methods and tools by including real examples from her experience building and deploying data science and AI projects. ...

Recent data shows that 87% of Artificial Intelligence/Big Data projects don’t make it into production (VB Staff, 2019), meaning that most projects are never deployed. This book addresses five common pitfalls that prevent projects from reaching deployment and provides tools and methods to avoid those pitfalls. Along the way, stories from actual experience in building and deploying data science projects are shared to illustrate the methods and tools. While the book is primar...

Agile Values and Principles for a New Generation“In the journey to all things Agile, Uncle Bob has been there, done that, and has the both the t-shirt and the scars to show for it. This delightful book is part history, part personal stories, and all wisdom. If you want to understand what Agile is and how it came to be, this is the book for you.”–Grady Booch“Bob’s frustration colors every sentence of Clean Agile, but it...

As data science evolves to become a business necessity, the importance of assembling a strong and innovative data teams grows. In this in-depth report, data scientist DJ Patil explains the skills, perspectives, tools and processes that position data science teams for success.Topics include: What it means to be "data driven." The unique roles of data scientists. The four essential qualities of data scientists. Patil's first-hand experience building the LinkedIn dat...

Master the hottest technology around to drive marketing successMarketers are faced with a stark and challenging dilemma: customers demand deep personalization, but they are increasingly leery of offering the type of personal data required to make it happen. As a solution to this problem, Customer Data Platforms have come to the fore, offering companies a way to capture, unify, activate, and analyze customer data. CDPs are the hottest marketing technology around tod...

Carefully researched over ten years and eagerly anticipated by the agile community, Crystal Clear: A Human-Powered Methodology for Small Teams is a lucid and practical introduction to running a successful agile project in your organization. Each chapter illuminates a different important aspect of orchestrating agile projects.Highlights includeAttention to the essential human and communication aspects of successful projectsCase studi...

In an era where AI can generate code in minutes, why do software teams still struggle to deliver?While artificial intelligence transforms how we build software, most organizations remain trapped by friction that turns AI's promise of speed into bottleneck nightmares. Slow deployments, brittle systems, and frustrated developers create invisible drag on innovation—costing US companies $1.52 trillion annually in technical debt alone.Frictionless: 7 Steps to Remove Barriers...

“We need better approaches to understanding and managing software requirements, and Dean provides them in this book. He draws ideas from three very useful intellectual pools: classical management practices, Agile methods, and lean product development. By combining the strengths of these three approaches, he has produced something that works better than any one in isolation.”–From the Foreword by Don Reinertsen, President of Reinertsen & Associates; author of M...

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice.In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatab...

Bringing a practitioner's view to big data analytics, this work examines the drivers behind big data, postulates a set of use cases, identifies sets of solution components, and recommends various implementation approaches. This work also addresses and thoroughly answers key questions on this emerging topic, including What is big data and how is it being used? How can strategic plans for big data analytics be generated? and How does big data change analytics architecture? ...

To continuously deliver IT systems at speed with a focus on business value, DevOps teams integrate quality engineering in their way of working. This book supports teams in implementing quality in their DevOps culture, with practical examples, useful knowledge and some theoretical background. For example, it describes how to benefit from a CI/CD pipeline. TMAP is the body of knowledge for quality engineering in IT delivery and builds on practical experience from thousands of people in more ...