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...