The importance of proper data structuring and preparation, which is usually called data preparation cannot be overemphasized, this is highly valuable and, oftentimes overlooked step, when training a model. This mistake is often made by newbies but it’s not unheard of for a more experienced data scientist. Today various organizations continue to look for ways to prepare their data quickly for their ML model and quickly solve their data problems. During my team’s first machine learning project we discovered we needed to do much on data preparation to get our training model to work better and more efficiently. …

Chukwuka Chime

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