Metaheuristics for Enterprise Data Intelligence [Hardcover]

Chapter 1 ? Terror Attacks Forecast Using Machine Learning and Neo4j Sandbox: A Review

Sagar Shinde, Suchitra Khoje, Ankit Raj and Lalitkumar Wadhwa

Chapter 2 ? 5G Evolution and Revolution: A Study

Namita K. Shinde, Chetan More, Payal Kadam and Vinod Patil

Chapter 3 ? Metaheuristic Algorithms and Its Application in Enterprise Data

Radhika D. Joshi, Sheetal Waghchaware and Rushikesh Dudhani

Chapter 4 ? Petrographic Image Classification Accuracy Improvement Using Improved Learning

Ashutosh Marathe, Tanuja Tewari and Falguni Vyas

Chapter 5 ? Data Visualization and Dashboard Design for Enterprise Intelligence

Nishikant Bhaskar Surwade, Bahubali Shiragapur and Anwar Hussain

Chapter 6 ? Beyond the Hype: Understanding the Potential of ChatGPT in the Articulation of Technical Papers

Neha Shaah

Chapter 7 ? Metaheuristics and Deep Learning in Lung Nodule Detection and Classification

Rama Vaibhav Kaulgud and Mandar Saundattikar

Chapter 8 ? An Improved Face Recognition Method Using Canonical Correlation Analysis

Ganesh D. Jadhav, Suhas Patil, Bhushan M. Borhade and Yogesh Shinde

Chapter 9 ? Guesswork to Results: How ML-Based A/B Testing Is Changing the Game

Namita K. Shinde, Payal Kadam, Aditya Choudhary, Bhavay Chopra and Krishnansh Awasthi

With the emergence of the data economy, information has become integral to business excellence. Every enterprise, irrespective of its domain of interest, carries and processes a lot of data in their day-to-day activities. Converting massive datasets into insightful information plays an important role in developing better business solutions. Data intelligence and its analysis pose several challenges in data lS+