When you build a Machine Learning model, first start with the data — make sure input data is prepared well and it represents the true state of what you want the Machine Learning model to learn. Data preparation task takes time, but don't hurry — quality data is key for Machine Learning success. In this post, I will go through the essential steps required to bring data into the right shape to feed it into a Machine Learning algorithm. Sample dataset and Python notebook for this post can be downloaded from my GitHub repo.


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python,ai,ml,pandas library