Buch, Englisch, 441 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 680 g
ICDSMLA 2022, 26-27 December, Hyderabad, India
Buch, Englisch, 441 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 680 g
Reihe: Lecture Notes in Electrical Engineering
ISBN: 978-981-99-2060-0
Verlag: Springer Nature Singapore
This book includes peer reviewed articles from the 4th International Conference on Data Science, Machine Learning and Applications, 2022, held at the Hyderabad Institute of Technology & Management on 26-27th December, India. ICDSMLA is one of the most prestigious conferences conceptualized in the field of Data Science & Machine Learning offering in-depth information on the latest developments in Artificial Intelligence, Machine Learning, Soft Computing, Human Computer Interaction, and various data science & machine learning applications. It provides a platform for academicians, scientists, researchers and professionals around the world to showcase broad range of perspectives, practices, and technical expertise in these fields. It offers participants the opportunity to stay informed about the latest developments in data science and machine learning.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
- Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
Weitere Infos & Material
Chapter 1: Mr. Bot – A Survey on Arduino Based Autonomous Robotic Vehicle.- Chapter 2: Opinion Mining based Fake Review Detection using Deep Learning Technique.- Chapter 3: Analysis of the Seer dataset for lung cancer diagnosis for Stage classification and survival Analysis.- Chapter 4: Data Analytics for Athlete Safety in Training.- Chapter 5: Social Media + Machine Learning to Offer Clues on Suicide Ideation Concerns.- Chapter 6: Analysis of Various Techniques of Fetal Growth Detection.