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If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous mathematics.
This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant... Læs mere
This book explores the rapid expansion of data sources, visualizations, and analytics created in the last decade and explores the strategies, tools, and approaches that educators and information specialists are employing to train a new generation of data professionals.
The book is intended for practitioners in data science and data analytics in both academic and business environments. It aims to present the reader with concepts in data science and analytics that were deemed to be more advanced or simply out of scope in the author's first book.
This is the first rigorous, self-contained treatment of the theory of deep learning. Aimed at scientists, instructors, and students interested in artificial intelligence and... Læs mere
This accessible and engaging book provides readers with the knowledge, experience, and confidence to work with raw data and unlock essential information (insights) from data summaries and visualisations.
Text is a fantastic resource for social scientists, but because it is so abundant, and so variable, it can be difficult to extract... Læs mere
Beginning-Intermediate user level
A practical introduction to setting up and conducting environmental research projects, with advice on how to effectively read scientific papers, develop... Læs mere
A practical introduction to setting up and conducting environmental research projects, with advice on how to effectively read scientific papers, develop... Læs mere