Deep Learning in Data Analytics: Recent Techniques, Practices and Applications
- Length: 286 pages
- Edition: 1
- Language: English
- Publisher: Springer
- Publication Date: 2021-08-12
- ISBN-10: 3030758540
- ISBN-13: 9783030758547
- Sales Rank: #0 (See Top 100 Books)
This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book’s material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society.
Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.
Cover Front Matter Part I. Theoretical Foundation of Deep Learning Theory and Analysis A Study on Discrete Action Sequences Using Deep Emotional Intelligence A Novel Noise Removal Technique Influenced by Deep Convolutional Autoencoders on Mammograms A High Security Framework Through Human Brain Using Algo Mixture Model Deep Learning Algorithm Knowledge Framework for Deep Learning: Congenital Heart Disease Part II. Computing System and Machine Learning Automatic Image Segmentation by Ranking Based SVM in Convolutional Neural Network on Diabetic Fundus Image Deep Learning in Healthcare On the Study of Machine Learning Algorithms Towards Healthcare Applications A Predictive Data Analytic Approach to Get Insight of Healthcare Databases Part III. Deep Learning Algorithms A Survey on Deep Learning Methodologies of Recent Applications An Extensive Study of Privacy Preserving Recommendation System Using Collaborative Filtering A Comparative Study of Nature-Inspired Algorithm Based Hybrid Neural Network Training Algorithms in Data Classification Anomaly Credit Card Fraud Detection Using Deep Learning Part IV. Applications of Deep Learning Techniques Application of Deep Learning for Energy Management in Smart Grid Cost Optimization of Software Quality Assurance Analytical Approach for Security of Sensitive Business Cloud
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