Buch, Englisch, 375 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 756 g
ICMLBDA 2023, NIT Arunachal Pradesh, India, May 29-30
Buch, Englisch, 375 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 756 g
Reihe: Springer Proceedings in Mathematics & Statistics
ISBN: 978-3-031-51341-1
Verlag: Springer
In the dynamic landscape of technology, machine learning and big data analytics have emerged as transformative forces, reshaping industries and empowering innovation. Machine learning, a subset of artificial intelligence, equips systems to learn and adapt from data, revolutionizing decision-making, automation, and predictive capabilities. Meanwhile, Big Data Analytics processes and extracts insights from vast and complex datasets, unveiling hidden patterns and trends. Together, these fields enable us to harness the immense power of data for smarter business strategies, improved healthcare, enhanced user experiences, and countless other applications. This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2023, which was held on May 29-30, 2023 by NERIST and NIT Arunachal Pradesh India) introduces an exciting journey into the intersection of machine learning and Big Data Analytics, where data becomes a catalyst for progress and transformation.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
- Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik Mathematik Stochastik Stochastische Prozesse
Weitere Infos & Material
Preface.- Optimized Neural Networks Archetype for Prediction of Socio-Economic Class of Women in India.- Improvement Of UPFC Performance In Power Systems Using Artificial Intelligence.- Classification of Parkinson’s Disease Using Machine Learning Techniques.- A Survey on Skin Cancer Detection Using Artificial Intelligence.- A Review of Ranking Approach to Rank Interval-valued Trapezoidal Intuitionistic Fuzzy Sets.- An Empirical Evaluation of ResNet-SE-16 for Accurate Classification of Lung Cancer using Histopathological Images.- Design of EV Battery System Using Grid-Interfaced Solar PV Power with Novel Adaptive Digital Control Algorithm.- A Decentralized and Intelligent Approach for Suspicious Event Detection in Surveillance Range.- Image Selection for Graphical Password Authentification.- Soft Computing for Visual Recognition through audio for Visually Impaired.- Diet Meal Plan Chatbot.- MRI Images Based Brain Tumor Classification Using Convolution Neural Networks.- Segmenting MRI Images Using Federated Learning for Brain Tumor Detection.- Comparative Analysis of Fuzzy Regular Graph Properties.- Effective Cloud Data Management by Using AES Encryption and Decryption.- Prediction of Angina Pectoris.- A Novel Web Attack Recognition System for IOT via Ensemble Classification.- Automatic Identification of Medical Plant Species Using VGG-19 Model.- Identification of Fake Job Recruitment Using Several Machine Learning (ML) Models.- SDS:Secure Image Transmission Using Advanced Encryption Standard With Salting, Steganography and Data Shredding Techniques.- Multi Crop – Multi Disease Detection.- Avian Soundscape Analysis Using Machine Learning.- Smart Security and Surveillance System.- Cyber Money Laundering Detection Using Machine Learning Methods.- Accessible chatbot Interface for Price Negotiation System.- Recognizing and Logging Vehicles by Scanning License Plates and Driver’s Face.- Machine learning based classification of X-ray images using convolutional neural networks.- A Comparative Study of Inception Models for Bone X-rays Classification and Pathology Detection.- Dietary Assessment Report Generation using RCNN.- A Blockchain based Networking Approach for Advanced HealthCare Services.- Fine-grained Sentiment Analysis on Covid-19 Tweets using Deep Learning Techniques.- Index.
