
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Computational Intelligence and its Applications
About this book
Computational Intelligence and its Applications explores cutting-edge advancements in machine learning, data science, and their practical applications. This comprehensive guide caters to college students, researchers, and professionals equipping readers with the knowledge to navigate and leverage the latest trends in computational intelligence effectively. Key Features:
- Emerging Technologies: Covers post-quantum cryptography, secure communication, and advancements in chatbot technology.
- Practical Applications: Includes stock price prediction, cloud computing, and data-driven DNA sequencing.
- Security and Detection: Enhances intrusion detection and analyzes crop disease using machine learning.
- Natural Language Processing: Explores sentiment analysis and the impact of big data on natural language processing.
- Advanced Techniques: Discusses blockchain technology, remote sensing, and depression detection on social media. Readership:
Ideal for academia and industry alike.
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Information
Table of contents
- Welcome
- Table of Contents
- Title
- BENTHAM SCIENCE PUBLISHERS LTD.
- PREFACE
- List of Contributors
- Emerging Frontiers: Post-Quantum Cryptography and Secure Communication
- Chatbot with Machine Learning: Latest Advancements
- Stock Price Prediction: A Gateway to a Prosperous Future Using Data Science and Machine Learning
- Cloud, Edge, and Fog Computing: A Study on their Broader Scope
- Data-Driven Approach of Species DNA Sequencing Based on Similar Patterns Using Machine Learning
- Enhancing Intrusion Detection Performance with a Hybrid Module on KDD99 Dataset
- A Comprehensive Study on Crop Disease Detection Using Machine Learning and Deep Learning Models
- Machine Learning Approaches for Natural Language Processing and Sentiment Analysis
- From Data to Big Data: An Exploration of the Evolution and Impact of Large-Scale Data Analytics
- Analysis Study on Blockchain Technology
- A Study on Remote Sensing Image Segmentation and Classification
- Depression Detection on Social Media Using the CNN-LSTM Model
- Evaluating Twitter Sentiments via Natural Language Processing