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Artificial Intelligence Basics: A Non-Technical Introduction
Artificial Intelligence Basics: A Non-Technical Introduction

Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and...

Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python
Natural Language Processing Recipes: Unlocking Text Data with Machine Learning and Deep Learning using Python
Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification,...
Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python
Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python
Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms...
Information Retrieval: Data Structures and Algorithms
Information Retrieval: Data Structures and Algorithms

Information retrieval is a sub-field of computer science that deals with the automated storage and retrieval of documents. Providing the latest information retrieval techniques, this guide discusses Information Retrieval data structures and algorithms, including implementations in C. Aimed at software engineers building systems with...

The Nature of Code: Simulating Natural Systems with Processing
The Nature of Code: Simulating Natural Systems with Processing
How can we capture the unpredictable evolutionary and emergent properties of nature in software? How can understanding the mathematical principles behind our physical world help us to create digital worlds? This book focuses on a range of programming strategies and techniques behind computer simulations of natural systems, from elementary...
Artificial Neural Networks with Java: Tools for Building Neural Network Applications
Artificial Neural Networks with Java: Tools for Building Neural Network Applications
Use Java to develop neural network applications in this practical book. After learning the rules involved in neural network processing, you will manually process the first neural network example. This covers the internals of front and back propagation, and facilitates the understanding of the main principles of neural...
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms

Key Features

  • Explore statistics and complex mathematics for data-intensive applications
  • Discover new developments in EM algorithm, PCA, and bayesian...
Super-Recursive Algorithms (Monographs in Computer Science)
Super-Recursive Algorithms (Monographs in Computer Science)
This book introduces the new realm of superrecursive algorithms and the development of mathematical models for them. Although many still believe that only recursive algorithms exist and that only some of them are realizable, there are many situations in which people actually work with superrecursive algorithms....
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications...
Modern Database Management (11th Edition)
Modern Database Management (11th Edition)
This text is designed to be used with an introductory course in database management. Such a course is usually required as part of an information systems curriculum in business schools, computer technology programs, and applied computer science departments. The Association for Information Systems (AIS), the Association...
Learning Linux Shell Scripting
Learning Linux Shell Scripting

Unleash the power of shell scripts to solve real-world problems by breaking through the practice of writing tedious code

About This Book

  • Learn how to efficiently and effectively build shell scripts and develop advanced applications with this handy book
  • Develop high...
Probabilistic Databases (Synthesis Lectures on Data Management)
Probabilistic Databases (Synthesis Lectures on Data Management)
Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of...
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