Audubon Wild Life Report
Machine Learning and Biometrics
We are entering the era of big data, and machine learning can be used to analyze this deluge of data automatically. Machine learning has been used to solve many interesting and often difficult real-world problems, and the biometrics is one of the leading applications of machine learning. This book introduces some new techniques on biometrics and machine learning, and new proposals of using machine learning techniques for biometrics as well. This book consists of two parts: "Biometrics" and "Mach...
Machine Learning
Business Intelligence and Agile Methodologies for Knowledge-Based Organizations: Cross-Disciplinary Applications highlights the marriage between business intelligence and knowledge management through the use of agile methodologies. Through its fifteen chapters, this book offers perspectives on the integration between process modeling, agile methodologies, business intelligence, knowledge management, and strategic management.
Use active machine learning with Python to improve the accuracy of predictive models, streamline the data analysis process, and adapt to evolving data trends, fostering innovation and progress across diverse fields Key Features Learn how to implement a pipeline for optimal model creation from large datasets and at lower costs Gain profound insights within your data while achieving greater efficiency and speed Apply your knowledge to real-world use cases and solve complex ML problems Purchase o...
Build simple, maintainable, and easy to deploy machine learning applications. About This Book • Build simple, but powerful, machine learning applications that leverage Go's standard library along with popular Go packages. • Learn the statistics, algorithms, and techniques needed to successfully implement machine learning in Go • Understand when and how to integrate certain types of machine learning model in Go applications. Who This Book Is For This book is for Go developers who are familiar...
Achieve TensorFlow certification with this comprehensive guide covering all exam topics using a hands-on, step-by-step approach—perfect for aspiring TensorFlow developers Key Features Build real-world computer vision, natural language, and time series applications Learn how to overcome issues such as overfitting with techniques such as data augmentation Master transfer learning—what it is and how to build applications with pre-trained models Purchase of the print or Kindle book includes a free...
This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising. The design of the DL models based on artificial neural networks is influenced by the structure and operation of the brain. This book presents a comprehensive resource for those who seek a solid grasp of the techniques in DL. Key features:Provides knowledge o...
Recommender Systems
by Dongsheng Li, Jianxun Lian, Le Zhang, Kan Ren, Tun Lu, Tao Wu, and Xing Xie
This book starts from the classic recommendation algorithms, introduces readers to the basic principles and main concepts of the traditional algorithms, and analyzes their advantages and limitations. Then, it addresses the fundamentals of deep learning, focusing on the deep-learning-based technology used, and analyzes problems arising in the theory and practice of recommender systems, helping readers gain a deeper understanding of the cutting-edge technology used in these systems. Lastly, it sha...
Neuro Symbolic Reasoning and Learning (SpringerBriefs in Computer Science)
by Paulo Shakarian, Chitta Baral, Gerardo I. Simari, Bowen Xi, and Lahari Pokala
This book provides a broad overview of the key results and frameworks for various NSAI tasks as well as discussing important application areas. This book also covers neuro symbolic reasoning frameworks such as LNN, LTN, and NeurASP and learning frameworks. This would include differential inductive logic programming, constraint learning and deep symbolic policy learning. Additionally, application areas such a visual question answering and natural language processing are discussed as well as top...
This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018. The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individua...
This LNCS conference volume constitutes the proceedings of the MICCAI Workshop GRAIL 2023 and MICCAI Challenge OCELOT 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, September 23, and October 4, 2023. The 9 full papers (GRAIL 2023) and 6 full papers (OCELOT 2023) included in this volume were carefully reviewed and selected from GRAIL 14 (GRAIL 2023) and 6 (OCELOT 2023) submissions. The conference GRAIL 2023 a wide set of methods and application and OCELOT 2023 focuses on th...
Master Machine Learning L lifecycle management with Oracle Cloud and you will be ready to implement ML driven applications. Key Features How to decide to make a decision about when to retrain How to observe the drifting patterns in ML models How to build cloud networks to support the relevant services and infrastructure Book DescriptionUnlock the full potential of your ML models with Oracle Cloud data science services. This guide provides a hands-on approach to managing the entire ML lifecycl...
Using Artificial Intelligence in the Search for Extraterrestrial Intelligence
by Srinivasa Rao Gundu and Panem Charanarur
This book introduces the Search for Extraterrestrial Intelligence (SETI), discusses its origins, and explores various research methods and resources for enthusiasts. It assesses SETI’s scientific legitimacy and ideas over the past three to four decades, arguing for complementary efforts in interstellar travel, alien societies, and intelligent life. As well as this, it raises the question of whether life on Earth is from an alien system, discusses hypothetical scenarios for successful communicati...
Open-Set Text Recognition (SpringerBriefs in Computer Science)
by Xu-Cheng Yin, Chun Yang, and Chang Liu
In real-world applications, new data, patterns, and categories that were not covered by the training data can frequently emerge, necessitating the capability to detect and adapt to novel characters incrementally. Researchers refer to these challenges as the Open-Set Text Recognition (OSTR) task, which has, in recent years, emerged as one of the prominent issues in the field of text recognition. This book begins by providing an introduction to the background of the OSTR task, covering essential a...
If you know how to program, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical formulas, using discrete probability distributions rather than continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer and you'll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not man...
Humanized AI (HAI), emerging as the next of the AI waves, refers to artificial social beings that are very close to humans in various aspects, beings who are machine-race humans, not digital slaves. Foundation, Architecture, and Prototyping of HAI deploy a novel smalldata approach to vertically explore the spectrum of HAI. Different from the popular big-data philosophy that is based on the rigid notion that the connotation of each concept is fixed and the same to everyone, this book treats und...
Advances in Deep Learning Applications for Smart Cities
Smart cities of the future must aspire to accommodate increasing technology and expectations of modern living, integrated societies, knowledge-based workforce, factory automation, and virtual-real social behaviors. This complex concoction of challenges requires new thinking of the synergistic utilization of reinforcement learning methods and data-driven decision making with automation infrastructure, autonomous transportation, connected buildings, smart homes, and embedded communities. Industri...
New Age Analytics
This comprehensive and timely book, New Age Analytics: Transforming the Internet through Machine Learning, IoT, and Trust Modeling, explores the importance of tools and techniques used in machine learning, big data mining, and more. The book explains how advancements in the world of the web have been achieved and how the experiences of users can be analyzed. It looks at data gathering by the various electronic means and explores techniques for analysis and management, how to manage voluminous da...
Intelligent Systems in Healthcare and Disease Identification using Data Science
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. This book is a descriptive summary of challenges and methods using disease identification with various case studies from diverse authors across the globe. One of the new buzzwords in healthcare sector that has become popular over years is health informatics. Healthc...