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1 vote

Gradient descent implementation of logistic regression

I think your implementation is correct and the answer provided is just wrong. Just for reference, the below figure represents the theory / math we are using here to implement Logistic Regression with ...
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1 vote

Predict data using Pre-Trained Classification Model

Yes. Whatever steps/processing you have done to the data before feeding it to the model, all of steps needs to be done again in the raw data. Ideally you should create a function which takes the data/...
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Why do we don't write units with MAE or RSME for regression problem ? If I wish to write the units when how do I identify the units for them?

RMSE and MAE do have units. In fact, they have the same units. (Determining why that’s the case is a useful exercise.) You determine those units by considering the units of your $y$. If $y$ is ...
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Why do we don't write units with MAE or RSME for regression problem ? If I wish to write the units when how do I identify the units for them?

In general evaluation measures don't have any unit. Many of them actually represent proportions of instances (like accuracy, precision, recall). But it's true that error evaluation measures are ...
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1 vote

LSTM basic doubt

First of all LSTM does not know the word it received, not at least in the sense that you think. LSTM like all neural net cell works with numeric vector representation. Even if you would build a ...
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1 vote

NLP logistic regression

This is a completely plausible model. You have five features (probably one-hot encoded) and then a categorical outcome. This is a reasonable place to use a (multinomial) logistic regression. Depending ...
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