Advancements in Machine Learning

This CCIS 2538 volume constitutes the proceedings of First and Second International Conference on Advancements in Machine Learning, ICCAML 2024, in Pune, India, during February 2829, 2024.

The 19 full papers are carefully reviewed and selected from 173 submissions. They were cartegorized under the topical sections as follows:

i) Modernization in Machine Learning

ii) Machine Learning for Data Analytics and

iii) Machine Learning for automation

Inhalt

Learning with Limited Data: A Machine Learning Approach for Heart Disease Prediction.- Enhanced Agricultural Crop Monitoring Using Autonomous Navigation Technologies.- Sandbox Based Real Time Cyber Attack Simulation and Analysis.- Dynamic Gesture Recognition Using LSTM for Real-time Indian Sign Language Prediction.- SpeechCraft: Modular AI Conversation System Using Multivariate LLMs.- An Extensive Investigation of Supervised Machine Learning (SML) Procedures aimed at Learners' Performance Forecast with Learning Analytics.- Leveraging Machine Learning Approaches for Enhanced Efficiency in Automated Processes.- Enhanced Pedestrian Detection for Autonomous Vehicles Using Multi-Localized Feature.- Enhancing lead score conversion rate using logistic regression.- Artificial Intelligence in Gestational Diabetes Mellitus.- A Comprehensive Risk Assessment Framework for Multiple Natural Hazards using CLIMADA Model.- A Review Paper on Image Forgery Detection Techniques.- Understanding Viewer Sentiment on Online Educational Content: An Analysis Framework for a Video Streaming Platform using Natural Language Processing.- Enhancing Crop Yield through Convolutional Neural Net-work (CNN) Powered Plant Disease Detection.- A Systematic Review on Anomaly Detection Techniques for Fog Computing Devices.- Supermarket Sales Prediction using Linear Regression: A Case Study Approach.- Employees performance metrics using Machine learning: A systematic literature review using Prisma Model.- WebGPU: Comparing Parallelism Over Serial Execution in Web Graphics.- Stock Market Prediction Technique through LSTM and NLP.