Waiting for the code example. Its a very interesting topic that could be applied for all e-commerce sellings when you have a huge portfolio and want to increase your profit
Standardization generally assumes that the underlying distribution is Gaussian. Standardization is also known as z-score normalization. Z-score tells how far a data point is from the mean of the distribution in terms of standard deviation. So, if the feature distribution is not Gaussian, it may not tell how far the data point is from the mean in terms of standard deviation, leading to misinterpretation of the results.
Appreciate this 👌
Waiting for the code example. Its a very interesting topic that could be applied for all e-commerce sellings when you have a huge portfolio and want to increase your profit
Overall question are good.
Waiting for newer and quite harder topics
Q. 3&4 were good, please try to add some mathematical questions and try to keep poll duration 3 days only.
Keep sharing article and mcqs on different topics in detail.
E.g. Standardization and Normalization maybe next topic
Thank you for the feedback. Will try to incorporate them in the best possible way.
Not the best explanation for a beginner, using visualization for both normal and gaussian distribution would have made it better
Normal and Gaussian distribution are same.
What happens if the feature distribution is not Gaussian and you still standardize?
Standardization generally assumes that the underlying distribution is Gaussian. Standardization is also known as z-score normalization. Z-score tells how far a data point is from the mean of the distribution in terms of standard deviation. So, if the feature distribution is not Gaussian, it may not tell how far the data point is from the mean in terms of standard deviation, leading to misinterpretation of the results.