Model deployment is the most important aspect of developing a machine learning product. The development of every product starts with an idea and then we check if it’s feasible or not. Once we are sure that it is feasible we gather the data and start developing a model for it. During the model development, we
Read MoreAs everything is getting digital the demand for machine-based document digitization is growing higher than ever. Every organization wants its documents to be digitized as digital documents are easy to search. Maintaining hard copies of documents is both an expensive and tedious process. Also, these documents become unreadable after some years due to the fact
Read MoreAccording to one research, 80% of the models built by data scientists never make it to production. The reason for this is that the production environment has several constraints. It could be inference time or it could be hardware in some cases. Hence, to make the model ready for production, we need to first think
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Data Engineering
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Business Intelligence & Tableau
