Machine learning Books

This book includes two manuscripts: Data Analytics for Businesses 2019 + Machine Learning for Beginners 2019.Are you looking for new ways to grow your business with resources you already have? Do you want to know how the big players like...

Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with easeKey Features:Understand 3D data processing with rendering, PyTorch optimization, and heterogeneous...

This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems.　It emphasizes applications of big data and IoT. It includes scientific...

Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners...

Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python.Key Features:Explore and create intelligent systems using cutting-edge deep learning techniquesImplement deep learning algorithms and work...

The processing of medical images in a reasonable timeframe and with high definition is very challenging. This volume helps to meet that challenge by presenting a thorough overview of medical imaging modalities, its processing, high-performance computing,...

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be able to solve problems with a...

Recommender systems are an important part of the information and e-commerce ecosystem. They represent a powerful method for enabling users to filter through large information and product spaces. Nearly two decades of research on collaborative filtering...

Lucidly Integrates Current Activities Focusing on both fundamentals and recent advances, Introduction to Machine Learning and Bioinformatics presents an informative and accessible account of the ways in which these two increasingly intertwined areas...

This book features techniques and real implementations of machine learning applications on Android phones. This book covers various developer tools, including TensorFlow and Google ML Kit. The book begins with a quick review of android...

Libro 1Este libro te presentará el mundo digital. La ciencia de datos es uno de los campos más sorprendentes y de tendencia en la era digital. La ciencia de datos es lo que nos hace humanos como somos hoy. No se limita a las tecnologías controladas por...

As industrial systems become more widespread, they are quickly becoming network-enabled, and their behavior is becoming more complex and intelligent. The Handbook of Research on Industrial Informatics and Manufacturing Intelligence: Innovations and...

Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable...

This book is designed as a reference book and presents a systematic approach to analyze evolutionary and nature-inspired population-based search algorithms. Beginning with an introduction to optimization methods and algorithms and various enzymes, the...

This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. It concentrates on cutting-edge research in DL and GAN which includes creating...

What Is AI?Why Will It Affect You?How Do You Survive and Thrive through the AI Revolution?Sensationalism about AI has reached new heights, and getting a useful understanding of it has never been more important. AI will extend and accelerate thinking,...

Cloud computing offers subscription-based on-demand services, and it has emerged as the backbone of the computing industry. It has enabled us to share resources among multiple users through virtualization, which creates a virtual instance of a computer...

Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing...

Provides a comprehensive analysis of the tools and techniques used for the development of efficient and robust decentralized infrastructures for various real-life scenarios, ranging from financial investment through blockchain protocols, shared...

Reinforcement learning (RL) is one of the foundational pillars of artificial intelligence and machine learning. An important consideration in any optimization or control problem is the notion of risk, but its incorporation into RL has been a fairly...

This textbook bridges this gap, providing an introduction to the mathematical foundations for the main algorithms used in machine learning for those from the physical sciences, without a formal background in computer science.

Brain Inspired Cognitive Systems 2008 (June 24-27, 2008; São Luís, Brazil) brought together leading scientists and engineers who use analytic, syntactic and computational methods both to understand the prodigious processing properties of biological...

A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system's perceived data, assisting scientists in the generation or...

Gain a competitive edge in today's data-driven world and build a rich career as a data professional that drives business success and innovation...Did you know that every minute, people around the world make 5.9 million searches on Google, share 1.7...

Course design myths and concerns debunkedHave you ever dreamed of creating a course? Whether it's online, in-person, or blended, designing an effective course can seem daunting. A web of myths and concerns often holds us back, limiting our ability to...

If you’re looking for a way to become an expert in machine learning, then keep reading...Machine learning is an incredibly dense topic. It’s hard to imagine condensing it into an easily readable and digestible format. However, this book aims...

Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learningKey FeaturesDevelop and deploy deep reinforcement learning-based solutions to production pipelines, products, and...

Master advanced techniques and algorithms for deep learning with PyTorch using real-world examplesKey Features- Understand how to use PyTorch 1.x to build advanced neural network models- Learn to perform a wide range of tasks by implementing deep...

Submodular functions are relevant to machine learning for at least two reasons: (1) some problems may be expressed directly as the optimization of submodular functions and (2) the Lovász extension of submodular functions provides a useful set of...

Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the...

Federated learning is a Distributed Machine Learning model that has been used in many applications today. Most edge devices can execute models with local dataset since their computation power is unutilized.

This book describes how AI techniques, such as deep learning, cognitive computing, and machine learning, can be used to analyze massive volumes of data produced by IoT devices in manufacturing environments.

This book explores computational engineering techniques and applications in agriculture development. Recent technologies such as cloud computing, IoT, big data, and machine learning are focused on for smart agricultural engineering. This book provides...

How can we leverage technology to uplift society while safeguarding our core values? This essential query is the central theme of the comprehensive essay anthology, "La Ecuación del Futuro: Equilibrio entre Humanidad y Tecnología" (Spanish Edition), by...

Unlocking Visual Insights: OpenCV Made Simple and Powerful.Book Description"Mastering OpenCV with Python" immerses you in the captivating realm of computer vision, with a structured approach that equips you with the knowledge and skills essential...

Analyze, Architect, and Innovate with Databricks LakehouseThe Databricks Lakehouse is groundbreaking technology that simplifies data storage, processing, and analysis. This cookbook offers a clear and practical guide to building and optimizing your...

This book reports research advances in the area of deep learning, IoT and urban computing, and describes new insights based on deep learning and IoT for urban computing.

SFCA/FPSAC (Series Formelles et Combinatoire Algebrique/Formal Power Se­ ries and Algebraic Combinatorics) is a series of international conferences that are held annually since 1988, alternating between Europe and North America...

This book presents state-of-the-art of optimization algorithms followed by internet of things (IoT) fundamentals. The applications of machine learning and IoT are explored, with topics such as optimization, algorithms, machine learning in image...

The book brings a blend of different areas of Machine Learning and the recent advances in the area. From the use of ML in healthcare to security, the book encompasses several areas related to ML while keeping a check on the traditional ML algorithms.

This book is a timely and critical introduction for people who are interested in what data science is (and isn't), and how it should be applied. The language is conversational and the content is accessible for readers without a quantitative or...

The health technology has become a hot topic in academic research. It employs the theory of social networks into the different levels of the prediction and analysis and has brought new possibilities for the development of technology.

Based on the research that has been conducted at Wharton Risk Management Center over the past five years on catastrophic risk. Covers a hot topic in the light of recent terroristic activities and nature catastrophes...