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Stay Ahead with Artificial Neural Network
~ Dr. Ashutosh Kumar Pandey
Till a few years ago, help features were the life support of tedious and complicated applications. As businesses move into the fast lane with time being a major constraint, the clichéd click-based directions provided by help files have become passé. Today, voicebased searches and voice-activated assistance has become the new normal. These appendages are powered by technologies such as Artificial Intelligence (AI) / Machine Learning (ML).
Similarly, as data proliferation is increasing, it is becoming highly important to seek out smarter ways of data analysis for continued progress to keep pace with the fast movers in the industry. In recent years, ML has emerged as the vital solution for skimming and analyzing humongous amounts of data to derive quick, actionable insights.
ML algorithms allow machines to recognize patterns, construct prediction models, or classify images or videos through learning. ML algorithms can be implemented using a wide variety of methods such as decision trees, random forest, clustering, neural network, and more. Artificial Neural Networks (ANNs) come under Deep Learning, which in nothing but ML, and ML is a subfield of AI.
Fast analysis and interpretation of unstructured data is what ANNs bring to the table in a fast paced, complex business environment.