So I've been getting into docker and for this, I've been following the docker documentation.So for my doubt, I've been specifically following this…
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for i in cnames: print(i) df_csv[i] = (df_csv[i] - min(df_csv[i]))/(max(df_csv[i]) - min(df_csv[i]))here df_csv is my dataset name
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To import Fast Text, we need only one line of data to train the word embedding.Let us try a word to fit in the model and see in the similarity
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First we import the libraries and the dataset # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd #…
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F1-Score is the harmonic mean of the precision and recall. Multiplying the constant of 2 scales the score to 1 when both precision and recall are 1.
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Grid search is an algorithm used for tuning a model by considering every hyperparameters specified and used for evaluating a model. It is used to…
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Logistic regression is a very popularly utilized classification technique in the credit and risk industry for checking the probability of default…
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NLP provided some of the developed libraries to implement Named Entity Recognition.
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Advantages Decision tree is comprehensive in nature as it forces the consideration of all possible outcomes of a decision and traces to a conclusion…
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To perform ROC on a model we need to train a model. bank
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Information gain is a measure of reduction in entropy caused by partitioning the examples according to a given attribute. The idea is to start with…
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if A>0.4 then if B0.8 then class='X' In order to extract the decision rules, we can use the following code. from sklearn.tree import _tree def…
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