Applied Cloud Deep Semantic Recognition
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Applied Cloud Deep Semantic Recognition
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Author : Mehdi Roopaei
language : en
Publisher: CRC Press
Release Date : 2018-04-09
Applied Cloud Deep Semantic Recognition written by Mehdi Roopaei and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-09 with Computers categories.
This book provides a comprehensive overview of the research on anomaly detection with respect to context and situational awareness that aim to get a better understanding of how context information influences anomaly detection. In each chapter, it identifies advanced anomaly detection and key assumptions, which are used by the model to differentiate between normal and anomalous behavior. When applying a given model to a particular application, the assumptions can be used as guidelines to assess the effectiveness of the model in that domain. Each chapter provides an advanced deep content understanding and anomaly detection algorithm, and then shows how the proposed approach is deviating of the basic techniques. Further, for each chapter, it describes the advantages and disadvantages of the algorithm. The final chapters provide a discussion on the computational complexity of the models and graph computational frameworks such as Google Tensorflow and H2O because it is an important issue in real application domains. This book provides a better understanding of the different directions in which research has been done on deep semantic analysis and situational assessment using deep learning for anomalous detection, and how methods developed in one area can be applied in applications in other domains. This book seeks to provide both cyber analytics practitioners and researchers an up-to-date and advanced knowledge in cloud based frameworks for deep semantic analysis and advanced anomaly detection using cognitive and artificial intelligence (AI) models.
Applied Cloud Deep Semantic Recognition
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Author : Mehdi Roopaei
language : en
Publisher: CRC Press
Release Date : 2018-04-09
Applied Cloud Deep Semantic Recognition written by Mehdi Roopaei and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-09 with Computers categories.
This book provides a comprehensive overview of the research on anomaly detection with respect to context and situational awareness that aim to get a better understanding of how context information influences anomaly detection. In each chapter, it identifies advanced anomaly detection and key assumptions, which are used by the model to differentiate between normal and anomalous behavior. When applying a given model to a particular application, the assumptions can be used as guidelines to assess the effectiveness of the model in that domain. Each chapter provides an advanced deep content understanding and anomaly detection algorithm, and then shows how the proposed approach is deviating of the basic techniques. Further, for each chapter, it describes the advantages and disadvantages of the algorithm. The final chapters provide a discussion on the computational complexity of the models and graph computational frameworks such as Google Tensorflow and H2O because it is an important issue in real application domains. This book provides a better understanding of the different directions in which research has been done on deep semantic analysis and situational assessment using deep learning for anomalous detection, and how methods developed in one area can be applied in applications in other domains. This book seeks to provide both cyber analytics practitioners and researchers an up-to-date and advanced knowledge in cloud based frameworks for deep semantic analysis and advanced anomaly detection using cognitive and artificial intelligence (AI) models.
Monetizing Machine Learning
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Author : Manuel Amunategui
language : en
Publisher: Apress
Release Date : 2018-09-12
Monetizing Machine Learning written by Manuel Amunategui and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-12 with Computers categories.
Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book—Amazon, Microsoft, Google, and PythonAnywhere. You will work through a series of common Python data science problems in an increasing order of complexity. The practical projects presented in this book are simple, clear, and can be used as templates to jump-start many other types of projects. You will learn to create a web application around numerical or categorical predictions, understand the analysis of text, create powerful and interactive presentations, serve restricted access to data, and leverage web plugins to accept credit card payments and donations. You will get your projects into the hands of the world in no time. Each chapter follows three steps: modeling the right way, designing and developing a local web application, and deploying onto a popular and reliable serverless cloud provider. You can easily jump to or skip particular topics in the book. You also will have access to Jupyter notebooks and code repositories for complete versions of the code covered in the book. What You’ll Learn Extend your machine learning models using simple techniques to create compelling and interactive web dashboards Leverage the Flask web framework for rapid prototyping of your Python models and ideas Create dynamic content powered by regression coefficients, logistic regressions, gradient boosting machines, Bayesian classifications, and more Harness the power of TensorFlow by exporting saved models into web applications Create rich web dashboards to handle complex real-time user input with JavaScript and Ajax to yield interactive and tailored content Create dashboards with paywalls to offer subscription-based access Access API data such as Google Maps,OpenWeather, etc. Apply different approaches to make sense of text data and return customized intelligence Build an intuitive and useful recommendation site to add value to users and entice them to keep coming back Utilize the freemium offerings of Google Analytics and analyze the results Take your ideas all the way to your customer's plate using the top serverless cloud providers Who This Book Is For Those with some programming experience with Python, code editing, and access to an interpreter in working order. The book is geared toward entrepreneurs who want to get their ideas onto the web without breaking the bank, small companies without an IT staff, students wanting exposure and training, and for all data science professionals ready to take things to the next level.
Applied Machine Learning For Data Science Practitioners
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Author : Vidya Subramanian
language : en
Publisher: John Wiley & Sons
Release Date : 2025-04-01
Applied Machine Learning For Data Science Practitioners written by Vidya Subramanian and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-01 with Mathematics categories.
A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML. Data Preparation covers the process of framing ML problems and preparing data and features for modeling. ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection. Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model. ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics. Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift.
Deep Learning Through Sparse And Low Rank Modeling
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Author : Zhangyang Wang
language : en
Publisher: Academic Press
Release Date : 2019-04-12
Deep Learning Through Sparse And Low Rank Modeling written by Zhangyang Wang and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-12 with Computers categories.
Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models-those that emphasize problem-specific Interpretability-with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely tied with the sparse/low rank methods and algorithms, providing a rich variety of theoretical and analytic tools to guide the design and interpretation of deep learning models. The development of the theory and models is supported by a wide variety of applications in computer vision, machine learning, signal processing, and data mining. This book will be highly useful for researchers, graduate students and practitioners working in the fields of computer vision, machine learning, signal processing, optimization and statistics.
Intelligent Systems And Human Machine Collaboration
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Author : Siddhartha Bhattacharyya
language : en
Publisher: Springer Nature
Release Date : 2023-03-29
Intelligent Systems And Human Machine Collaboration written by Siddhartha Bhattacharyya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-29 with Computers categories.
The book constitutes proceedings of the International Conference on Intelligent Systems and Human-Machine Collaboration 2022. The papers consist of research from different domains of human-machine interaction, computer engineering like quantum computational intelligence, big data analytics, the Internet of things, etc. The book includes significant contributions from academia and industry dealing with human-machine interaction both from the theoretical development and the application point of view. It also brings out research articles in interdisciplinary platforms applying human-machine interaction. The book is useful to researchers and practitioners alike.
Computer Vision Eccv 2018 Workshops
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Author : Laura Leal-Taixé
language : en
Publisher: Springer
Release Date : 2019-01-22
Computer Vision Eccv 2018 Workshops written by Laura Leal-Taixé and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-22 with Computers categories.
The six-volume set comprising the LNCS volumes 11129-11134 constitutes the refereed proceedings of the workshops that took place in conjunction with the 15th European Conference on Computer Vision, ECCV 2018, held in Munich, Germany, in September 2018.43 workshops from 74 workshops proposals were selected for inclusion in the proceedings. The workshop topics present a good orchestration of new trends and traditional issues, built bridges into neighboring fields, and discuss fundamental technologies and novel applications.
Geospatial Intelligence
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Author : Fatimazahra Barramou
language : en
Publisher: Springer Nature
Release Date : 2021-11-10
Geospatial Intelligence written by Fatimazahra Barramou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-10 with Computers categories.
This book explores cutting-edge methods combining geospatial technologies and artificial intelligence related to several fields such as smart farming, urban planning, geology, transportation, and 3D city models. It introduces techniques which range from machine and deep learning to remote sensing for geospatial data analysis. The book consists of two main parts that include 13 chapters contributed by promising authors. The first part deals with the use of artificial intelligence techniques to improve spatial data analysis, whereas the second part focuses on the use of artificial intelligence with remote sensing in various fields. Throughout the chapters, the interest for the use of artificial intelligence is demonstrated for different geospatial technologies such as aerial imagery, drones, Lidar, satellite remote sensing, and more. The work in this book is dedicated to the scientific community interested in the coupling of geospatial technologies and artificial intelligence and exploring the synergetic effects of both fields. It offers practitioners and researchers from academia, the industry and government information, experiences and research results about all aspects of specialized and interdisciplinary fields on geospatial intelligence.
Proceedings Of The 3rd International Conference On Machine Learning Cloud Computing And Intelligent Mining Mlccim2024
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Author : Fuchun Sun
language : en
Publisher: Springer Nature
Release Date : 2025-02-05
Proceedings Of The 3rd International Conference On Machine Learning Cloud Computing And Intelligent Mining Mlccim2024 written by Fuchun Sun and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-05 with Technology & Engineering categories.
The proceedings offer a meticulously curated compilation of peer-reviewed papers presented at the 3rd International Conference on Machine Learning, Cloud Computing and Intelligent Mining (MLCCIM2024). With a profound focus on these domains, this volume serves as an invaluable resource for researchers, experts, professionals, and practitioners engaged in machine learning, control systems, robot, cloud computing and intelligent mining techniques. The conference facilitated a vibrant exchange of knowledge, enabling participants to unveil their pioneering research findings, showcase the outcomes of their latest projects, and engage in thought-provoking discussions to share perspectives and experiences.
Proceedings Of 2023 Chinese Intelligent Automation Conference
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Author : Zhidong Deng
language : en
Publisher: Springer Nature
Release Date : 2023-09-22
Proceedings Of 2023 Chinese Intelligent Automation Conference written by Zhidong Deng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-22 with Technology & Engineering categories.
The book presents selected research papers from the 2023 Chinese Intelligent Automation Conference (CIAC2023), held in Nanjing, China, on October 2-5, 2023. It covers a wide range of topics including intelligent control, robotics, artificial intelligence, pattern recognition, unmanned systems, IoT, and machine learning. It includes original research and the latest advances in the field of intelligent automation. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in this field.