European Journal of Biomedical and Pharmaceutical Sciences

ARTIFICIAL INTELLIGENCE FOR FUTURE ASPECTS IN PHARMACEUTICALS- A REVIEW

Gowrish Ramakrishnan, Ashnaa Selvakumar, Venkatesh Sakkarapani, Sattanathan Kumar* and
Jeevanandham Somasundaram

ABSTRACT

AI is the ability of a machine to display human-like intelligence to perform various tasks, like planning, reasoning, creativity, and planning. Today, you can see AI being implemented in self-driving cars, adaptive learning machines, mobile applications, chatbots, and various other applications. Artificial Intelligence (A.I.) is defined as the ability of a machine to perform cognitive functions that we associate with human minds, such as perceiving, reasoning, learning, interacting with the environment, problem solving, decision-making, and even demonstrating creativity. AI data classification is a process where AI systems are trained to categorize data into predefined classes or labels. By learning from patterns in historical data, AI classification sorts through vast amounts of data, creating order from the digital chaos. The popularity of machine learning (ML), deep learning (DL) and artificial intelligence (AI) has risen sharply in recent years. Despite this spike in popularity, the inner workings of ML and DL algorithms are often perceived as opaque, and their relationship to classical data analysis tools remains debated Machine Learning is a subset of artificial intelligence that helps you build AI-driven applications. Deep Learning is a subset of machine learning that uses vast volumes of data and complex algorithms to train a model. Machine Learning is a subset of artificial intelligence that helps you build AI-driven applications. Deep Learning is a subset of machine learning that uses vast volumes of data and complex algorithms to train a model.

Keywords: Artificial Intelligence, Machine Learning, Deep Learning.