Deep Learning in Data Analytics -

Deep Learning in Data Analytics

Recent Techniques, Practices and Applications
Buch | Hardcover
XX, 266 Seiten
2021 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-030-75854-7 (ISBN)
181,89 inkl. MwSt

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.

lt;p>

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.- Computing System and Machine Learning.- Automatic Image Segmentation by Ranking based SVM in Convolutional Neural Network on Diabetic Fundus Image.

Erscheinungsdatum
Reihe/Serie Studies in Big Data
Zusatzinfo XX, 266 p. 114 illus., 92 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 589 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik
Schlagworte Computational Intelligence • Data Mining • Deep learning • Deep Learning Algorithms • Deep Learning Applications • Deep Learning Concepts • Deep Networks • Discovery Databases • Image Processing • Intelligent system • Kernel learning • Knowledge • Knowledge Representation • machine learning • Management Decision Making • representation learning • supervised learning • Unsupervised Learning
ISBN-10 3-030-75854-0 / 3030758540
ISBN-13 978-3-030-75854-7 / 9783030758547
Zustand Neuware
Haben Sie eine Frage zum Produkt?
Mehr entdecken
aus dem Bereich
Datenanalyse für Künstliche Intelligenz

von Jürgen Cleve; Uwe Lämmel

Buch | Softcover (2024)
De Gruyter Oldenbourg (Verlag)
74,95
Auswertung von Daten mit pandas, NumPy und IPython

von Wes McKinney

Buch | Softcover (2023)
O'Reilly (Verlag)
44,90