ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774

APPLYING MACHINE LEARNING TECHNIQUES TO ASSESS THE QUALITY OF TECHNICAL PAPERS 

Abstract

Artificial intelligence, much like statistics and calculus, has become a valuable tool in engineering and experimental research. The pillars of data science—deep learning, artificial intelligence, and Machine Learning [ML] —are pivotal for scholars in this rapidly expanding field. This article elucidates the interconnections among these foundational elements of data science. Machine Learning [ML] serves as a prerequisite for any analytical endeavor, and this article delves into the process of building Machine Learning [ML] models from scratch. Deep learning, often referred to as the latest wave in machine intelligence, receives special attention, with an exploration of its fundamental architecture. Furthermore, the report conducts a proportional analysis among deep knowledge & Machine Learning [ML] , offering researchers a comprehensive viewpoint. Keywords: Machine Learning [ML] , Deep learning, Artificial Intelligence, shallow learning.

Full Text PDF

IMPORTANT DATES

Submit paper at ijasret@gmail.com

Paper Submission Open For 2026
UGC indexed in (Old UGC) 2017
Last date for paper submission 31 DEC 2026
Deadline Submit the paper anytime.
Publication of Paper Within 15-30 Days after completing all the formalities