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The development in the field of technology has enhanced over the years. With time, we get terms like Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) in technology. AI has been a part of the research lab and scientific study for decades-ever since computer scientists initially rolled out the term in 1956. Since then, AI has been heralded as the future of human civilisation. AI describes as a machine that is capable of imitating and performing intelligent human behaviour. It is reckoned to be one of the most important major industrial revolutions that bring a dramatic impact on many fields such as business, healthcare, robotics, and manufacturing. With the explosion of big data analytics, more and more companies are adopting AI to drive decision making in organisations and improve operational efficiency. Machine learning is a part of AI. ML describes as machines that are taught to learn and make a decision by examining large amounts of input data. The more information a program has to browse through, the easier it is for that solution to make decisions and answer essential questions. Deep learning is a subset of ML. The difference between the two is that ML needs some guidance for performing a task, whereas DL is a model that will do it without the interference of programmers. DL is far more complex and accurate than ML, it’s also more expensive. Scientists need massive data sets to train neural networks because there are a vast number of parameters for any learning algorithm to understand before it can make accurate choices. This model is loosely patterned after the brain’s neural networks and has been setting new records of accuracy when applied to sound and image recognition.