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News headlines about privacy invasions, discrimination, and biases discovered in the platforms of big technology companies are commonplace today, and big tech's reluctance to …
Fay and Brittain present statistical hypothesis testing and compatible confidence intervals, focusing on application and proper interpretation. The emphasis is on equipping applied …
Data assimilation is a hugely important mathematical technique, relevant in fields as diverse as geophysics, data science, and neuroscience. This modern book provides an …
This book presents a unified theory of random matrices for applications in machine learning, offering a large-dimensional data vision that exploits concentration and universality …
Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic optimization techniques and their fundamental …
Chunyan Li is a course instructor with many years of experience in teaching about time series analysis. His book is essential for students and researchers in oceanography and other …
Data science is the foundation of our modern world. It underlies applications used by billions of people every day, providing new tools, forms of entertainment, economic growth, …
Healthcare has recently seen numerous exciting applications of artificial intelligence, industrial engineering, and operations research. This book, designed to be accessible to a …
Every day we interact with machine learning systems offering individualized predictions for our entertainment, social connections, purchases, or health. These involve several …
All social and policy researchers need to synthesize data into a visual representation. Producing good visualizations combines creativity and technique. This book teaches the …