Machine learning (ML) is a category of algorithm that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output while updating outputs as new data becomes available.
Continued research into deep learning and AI is increasingly focused on developing more general applications. Today’s AI models require extensive training in order to produce an algorithm that is highly optimized to perform one task. But some researchers are exploring ways to make models more flexible and able to apply context learned from one task to future, different tasks.This internship provides an overview to understand Machine learning and how it is developing with time. The guide aims at introducing the fundamentals of Machine Learning its practical applications and working. The student will gain knowledge through hands-on session, under the direction of Industry expert Trainers.