Harmonizing Neural Networks and Machine Learning: an In-Depth Investigation into the Synergy of Artificial Intelligence

EasyChair Preprint 12030

Abstract

This research paper delves into the intricate interplay between neural networks and machine learning, aiming to unravel the synergistic potential inherent in the fusion of these two pillars of artificial intelligence (AI). Through an in-depth investigation, we explore the nuanced relationships, challenges, and breakthroughs that arise when harmonizing neural networks with traditional machine learning techniques. Our analysis spans various applications, including image recognition, natural language processing, and predictive analytics. By elucidating the synergies between neural networks and machine learning, we aim to contribute to the evolving landscape of AI, fostering a deeper understanding of the combined capabilities that can propel the field forward.

Keyphrases: Artificial Intelligence, Cognitive Computing, Computational Intelligence, Integration, Predictive Analytics, deep learning, interdisciplinary, machine learning, neural networks, synergy

@booklet{EasyChair:12030,
  author    = {Deep Himmatbhai Ajabani},
  title     = {Harmonizing Neural Networks and Machine Learning: an In-Depth Investigation into the Synergy of Artificial Intelligence},
  howpublished = {EasyChair Preprint 12030},
  year      = {EasyChair, 2024}}