Artificial intelligence trends for data analytics using machine learning and deep learning approaches
著者
書誌事項
Artificial intelligence trends for data analytics using machine learning and deep learning approaches
(Artificial intelligence (AI) : elementary to advanced practices / series editors, Vijender Kumar Solanki, Zhongyu (Joan) Lu, and Valentina E. Balas)
CRC Press, 2021
- : hbk
大学図書館所蔵 全2件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems.
The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications.
Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems.
Features
Includes AI-based decision-making approaches
Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images
Covers automation of systems through machine learning and deep learning approaches and its implications to the real world
Presents data analytics and mining for decision-support applications
Offers case-based reasoning
目次
1. An Artificial Intelligence System Based Power Estimation Method for CMOS VLSI Circuits 2. Awareness Alert and Information Analysis in Social Media Networking Using Usage Analysis and Negotiable Approach 3. Object Detection and Tracking in Video Using Deep Learning Techniques: A Review 4. Fuzzy MCDM: Application in Disease Risk and Prediction 5. Deep Learning Approach to Predict and Grade Glaucoma from Fundus Images through Constitutional Neural Networks 6. A Novel Method for Securing Cognitive Radio Communication Network Using the Machine Learning Schemes and a Rule Based Approaches 7. Detection of Retinopathy of Prematurity Using Convolution Neural Network 8. Impact of Technology on Human Resource Information System and Achieving Business Intelligence in Organizations 9. Proficient Prediction of Acute Lymphoblastic Leukemia Using Machine Learning Algorithm 10. Role of Machine Learning in Social Area Networks 11. Breast Cancer and Machine Learning: Interactive Breast Cancer Prediction Using Naive Bayes Algorithm 12. Deep Networks and Deep Learning Algorithms 13. Machine Learning for Big Data Analytics, Interactive and Reinforcement 14. Fish Farm Monitoring System Using IoT and Machine Learning
「Nielsen BookData」 より