Algorithms Books


Haskell Notes for Professionals

Haskell

The Haskell Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow.

C++ Notes for Professionals

C / C++

The C++ Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow.

Digital Signal Processing

Python MATLAB Octave

This practical guide bridges the core concepts of Digital Signal Processing (DSP) and modern digital communications. It focuses on the implementation of these principles using open-source tools like Python, Octave, and GNU Radio, alongside low-cost hardware platforms (USRP, DVB-T dongles, HackRF). The book takes a hands-on, code-first approach to b

First Semester in Numerical Analysis with Julia

Julia Analysis

First Semester in Numerical Analysis with Julia presents the theory and methods, together with the implementation of the algorithms using the Julia programming language. The open access book covers computer arithmetic, root-finding, numerical quadrature and differentiation, and approximation theory. The reader is expected to have studied calculus a

Entity-Oriented Search

This open access book covers all facets of entity-oriented search - where "search" can be interpreted in the broadest sense of information access - from a unified point of view, and provides a coherent and comprehensive overview of the state of the art. It represents the first synthesis of research in this broad and rapidly developing area. Selecte

Real-Time Systems Development with RTEMS and Multicore Processors

The proliferation of multicore processors in the embedded market for Internet-of-Things (IoT) and Cyber-Physical Systems (CPS) makes developing real-time embedded applications increasingly difficult. What is the underlying theory that makes multicore real-time possible? How does theory influence application design? When is a real-time operating sys

Elements of Data Science

Python

Elements of Data Science is an introduction to the practical skills of working with data, written for people with no programming experience. Concepts are explained clearly and concisely, and exercises in each chapter demonstrate the real-world use of each feature. - Step-by-Step Approach: Learn how to execute a data science project from start to fi

Statistical Analysis of Networks

Statistics

This open book is a general introduction to the statistical analysis of networks, and can serve both as a research monograph and as a textbook. Numerous fundamental tools and concepts needed for the analysis of networks are presented, such as network modeling, community detection, graph-based semi-supervised learning and sampling in networks. The d

Information Theory for Data Science

Information theory deals with mathematical laws that govern the flow, representation and transmission of information, just as the field of physics concerns laws that govern the behavior of the physical universe. The foundation was made in the context of communication while characterizing the fundamental limits of communication and offering codes (s