Deep Learning in Data Analytics

Recent Techniques, Practices and Applications
Herausgeber: Acharjya, Debi Prasanna; Mitra, Anirban; Zaman, Noor

• Broschiertes Buch

Produktbeschreibung

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.

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Studies in Big Data Nr.91
• Verlag: Springer International Publishing / Springer International Publishing AG
• 1st ed. 2022
• Seitenzahl: 288
• Erscheinungstermin: 13. August 2022
• Englisch
• Abmessung: 235mm x 155mm x 16mm
• Gewicht: 441g
• ISBN-13: 9783030758578
• ISBN-10: 3030758575
• Artikelnr.: 64361456

Autorenporträt

Inhaltsangabe

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.