This textbook presents fundamental machine learning concepts in an easy to understand manner by providing practical advice, using straightforward examples, and offering engaging discussions of relevant applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, neural ...
This book covers the content of European postgraduate spine surgery courses, using a case-based approach. A step-wise solution to a real clinical problem is described and compared to the best available evidence. A weighted conclusion is provided on how to bridge the gap (if there is one) between standard of care and evidence-based medicine.Spine Su...
This book covers both classical and modern models in deep learning. The chapters of this book span three categories:
The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional mac...
This carefully written textbook offers a thorough introduction to abstract algebra, covering the fundamentals of groups, rings and fields. The first two chapters present preliminary topics such as properties of the integers and equivalence relations. The author then explores the first major algebraic structure, the group, progressing as far as the ...
This book considers all aspects of managing the complexity of Multimedia Big Data Computing (MMBD) for IoT applications and develops a comprehensive taxonomy. It also discusses a process model that addresses a number of research challenges associated with MMBD, such as scalability, accessibility, reliability, heterogeneity, and Quality of Service (...
This book is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning.With careful treatment of topics that fill the curricular needs for the course, Probab...
This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual...
A deep learning is of great interest these days, the crucial necessity for rapid and optimized implementation of the algorithms and designing architectures is the software environment. TensorFlow is designed to facilitate this goal. The strong advantage of TensorFlow is it flexibility is designing highly modular model which also can be a disadvanta...
The C Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow....
Big Data collected by customer-facing organisations - such as smartphone logs, store loyalty card transactions, smart travel tickets, social media posts, or smart energy meter readings - account for most of the data collected about citizens today. As a result, they are transforming the practice of social science. Consumer Big Data are distinct from...
Welcome to Writing Unleashed, designed for use as a book in first-year college composition programs, written as an extremely brief guide for students, jam-packed with teachers' voices, students' voices, and engineered for fun....
This open book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Informatics (NII), Japan. The book is unique in that it discusses not just what was done at NTCIR, but also how ...
This open book maps a crucial but neglected chapter in the history of psychiatry: how was melancholia transformed in the nineteenth century from traditional melancholy madness into a modern biomedical mood disorder, paving the way for the emergence of clinical depression as a psychiatric illness in the twentieth century? At a time when the prevalen...
This open book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emergin...
This open book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introdu...
Types are the central organizing principle of the theory of programming languages. Language features are manifestations of type structure. The syntax of a language is governed by the constructs that define its types, and its semantics is determined by the interactions among those constructs. The soundness of a language design - the absence of ill-d...
How do university finances really work?
From flagship public research universities to small, private liberal arts colleges, there are few aspects of these institutions associated with more confusion, myths or lack of understanding than how they fund themselves and function in the business of higher education. Using simple, approachable explanati...
This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packe...
This is an intro to C for folks who already know how to program in another language. The first half of the book is written in a tutorial style, while the second half is a reference section complete with examples (inspired by the incomparable Turbo C Bible). The goal is to keep this up-to-date with the latest C standards.
This guide assumes that ...
The world of machine learning is evolving so quickly that it's challenging to find real-life use cases that are relevant to your day-to-day work.
That's why we've created this comprehensive guide you can start using right away. Get everything you need - use cases, code samples and notebooks - so you can start putting the Databrick...
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent inte...