Many industries are trying to adopt new technologies that could make their work easier, more efficient, and cost-effective. That is how Artificial Intelligence (AI) and Machine Learning (ML) come into play. These two technologies are already used in many industries such as health care, finance, entertainment, automobile, e-commerce, etc and they will soon create a revolution that we have never seen before. With that being said, AI and ML are not as easy as we all think. It requires structured datasets for the algorithms to train the machine learning systems to recognize, identify and deliver accurate output.
Data labeling and its significance
Before we get deeper into machine learning and artificial intelligence, first let us know what data labeling is. Data labeling or data annotation is the process of creating structured datasets for algorithms to train the machine learning models to detect and recognize objects with accuracy. In simple terms, it is the process of converting unstructured data to structured datasets.
Data annotation and labeling have gained immense popularity in recent times due to their method of processing. Many industries have been beneficial and are now looking forward to implementing these technologies in other fields in order to welcome new business opportunities. Once implemented, AI and ML will save you a lot of time and money and will also give you accurate results.
There are many techniques that are currently being used to train supervised machine learning
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