Abhishek Swaroop,
Zdzislaw Polkowski,
Sérgio Duarte Correia,
Bal Virdee
e.a.
Springer Nature Singapore
e druk, 2024
9789819965434
Proceedings of Data Analytics and Management
ICDAM 2023, Volume 1
Specificaties
Paperback, blz.
|
Engels
Springer Nature Singapore |
e druk, 2024
ISBN13: 9789819965434
Rubricering
Onderdeel van serie
Lecture Notes in Networks and Systems
Verwachte levertijd ongeveer 9 werkdagen
Samenvatting
This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2023), held at London Metropolitan University, London, UK, during June 2023. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. The book is divided into four volumes.
Specificaties
ISBN13:9789819965434
Taal:Engels
Bindwijze:paperback
Uitgever:Springer Nature Singapore
Inhoudsopgave
Chapter 1: Diagnosis of Parkinson disease using Ensemble methods for Class Imbalance Problem.- Chapter 2: A Comparative Analysis of Pneumonia Detection Using Chest X-Rays With DNN.- Chapter 3: Machine Learning Based Binary Sentiment Classification of Movie Reviews in Hindi (Devanagari Script).- Chapter 4: Deep Learning-Based Recommendation Systems: Review and Critical Analysis.- Chapter 5: Retention in Second Year Computing Students in a London-Based University During The Post-Covid-19 Era Using Learned Optimism as a Lens: A Statistical Analysis in R.- Chapter 6: Alzheimer’s Disease Knowledge Graph Based on Ontology and Neo4j Graph Database.- Chapter 7: Forecasting Bitcoin Prices in the Context of the COVID19 Pandemic Using Machine Learning Approaches.- Chapter 8: Online Food Delivery Customer Churn Prediction: A Quantitative Analysis on the Performance of Machine Learning Classifiers.- Chapter 9: Prevention Equipment for COVID-19 Spread Using IoT and Multimedia-Based Solutions.- Chapter 10: Renal Disease Classification using Image Processing. etc.
