Book picks similar to
Sampling by Steven K. Thompson
statistics
academia
probability-statistics
sampling
Mastering ArcGIS
Maribeth H. Price - 2003
The author's step-by-step approach helps students negotiate the challenging tasks involved in learning sophisticated GIS software. The fifth edition is updated to follow the new software release of ArcGIS 10. An innovative and unique feature of "Mastering ArcGIS" is its accompanying CD-ROM with narrated video clips that show students exactly how to perform chapter tutorials before attempting an exercise on their own.
The Grammar of English Grammars
Goold Brown - 2011
You may find it for free on the web. Purchase of the Kindle edition includes wireless delivery.
Deep Learning
Ian Goodfellow - 2016
Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.