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AI/ML models are becoming an essential enterprise priority. However, for these smart models to perform in-depth analysis and make sense out of the datasets, t require supervised training. A strategic combination of human experience and advanced tools is needed to train these data-driven models. Data sets have to be labeled properly to be fed into the computer vision-based models, highlighting the importance of data annotation. Putting it simply, data annotation is the process of adding tags and metatags to the input training sets. This helps smart models to identify the object of interest easily and yield reliable results. The team of accredited annotators at Damco develops enhanced datasets to be fed into the machine learning algorithms. T create the training environment similar to the model’s future use case to help it calculate attributes easily.
Annotate PDF: All You Need to Know
One of the major requirements of AI is that the data set needs to be labeled at different levels of resolution. In the present scenario, you can create an annotated data set that can be used to train various machine learning methods. DAACO's dataset and methods are already being utilized. To train advanced models without any further human input, DAACO uses supervised training. In the data annotation phase, supervised training will be performed using deep reinforcement learning. DAACO is looking to leverage its dataset to train its machine learning models.
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