MACHINE LEARNING
found 109 books
Computational Conflict Research
by Emanuel Deutschmann, Jan Lorenz, Luis G. Nardin, Davide Natalini, Adalbert F. X. Wilhelm
This free book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machine learning to agent-based modelling and social network an...
Annotated Algorithms in Python
by Massimo Di Pierro
This book is assembled from lectures given by the author over a period of 10 years at the School of Computing of DePaul University. The lectures cover multiple classes, including Analysis and Design of Algorithms, Scientific Computing, Monte Carlo Simulations, and Parallel Algorithms. These lectures teach the core knowledge required by any scientis...
The Linux Command Line
by William Shotts
The Linux Command Line takes you from your very first terminal keystrokes to writing full programs in Bash, the most popular Linux shell (or command line). Along the way you'll learn the timeless skills handed down by generations of experienced, mouse-shunning gurus: file navigation, environment configuration, command chaining, pattern matchin...
Introduction to Logic Circuits & Logic Design with Verilog
by Brock J. LaMeres
This book for courses in Digital Systems Design introduces students to the fundamental hardware used in modern computers. Coverage includes both the classical approach to digital system design (i.e., pen and paper) in addition to the modern hardware description language (HDL) design approach (computer-based). Using this textbook enables readers to ...
Introduction to Logic Circuits & Logic Design with Verilog
by Brock J. LaMeres
This book for courses in Digital Systems Design introduces students to the fundamental hardware used in modern computers. Coverage includes both the classical approach to digital system design (i.e., pen and paper) in addition to the modern hardware description language (HDL) design approach (computer-based). Using this textbook enables readers to ...
Quick Start Guide to VHDL
by Brock J. LaMeres
This book provides a starter's guide to VHDL. This book can be used in conjunction with a one-semester course in Digital Systems Design or on its own for designers who only need an introduction to the language. This book is designed to provide a bottoms-up approach to learning the VHDL language. This design supports a course in which foundatio...
Quick Start Guide to Verilog
by Brock J. LaMeres
This book provides a starter's guide to Verilog, to be used in conjunction with a one-semester course in Digital Systems Design, or on its own for readers who only need an introduction to the language. This book is designed to match the way the material is actually taught in the classroom. Topics are presented in a manner which builds foundati...
Introduction to Logic Circuits & Logic Design with VHDL
by Brock J. LaMeres
This textbook introduces readers to the fundamental hardware used in modern computers. The only pre-requisite is algebra, so it can be taken by college freshman or sophomore students or even used in Advanced Placement courses in high school. This book presents both the classical approach to digital system design (i.e., pen and paper) in addition ...
Probability and Statistics for Computer Science
by David Forsyth
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...
TensorFlow Roadmap
by Amirsina Torfi
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...