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100-days-of-machine-learning's Issues

df.append is not working in Standardization

6200 and name not in self._accessors
6201 and self._info_axis._can_hold_identifiers_and_holds_name(name)
6202 ):
6203 return self[name]
-> 6204 return object.getattribute(self, name)

AttributeError: 'DataFrame' object has no attribute 'append'

having this error. So i got a solution for it.
`data_to_append = {'Age': [5, 90, 95], 'EstimatedSalary': [1000, 250000, 350000], 'Purchased': [0, 1, 1]}

df_to_append = pd.DataFrame(data_to_append)

df = pd.concat([df, df_to_append], ignore_index=True)

print(df.describe())`

You can update the file, so others can't face this issue.

Issue in code

There is an issue in code at line number 4
as it must be temp_df.head() instead of df.head()
please consider this and change the code

Batch size not mentioned in Mini-Batch GD

For Mini-batch GD, the coef_der = -2 * (value) according to the code.

** It should be coef_der = -2/self.batch_size * (value) **

n=1 in SGD and n = X_train.shape[1] in Batch. So, it should be n = self.batch_size in Mini-batch GD.

Issue on day 45 while Feature Splitting

in the day 45 while doing groupby of 'Title and Survived' Error is occuring because of datatype.

Error can be solved by using this code.

`df['Survived'] = pd.to_numeric(df['Survived'], errors='coerce') # Convert to numeric, coerce errors to NaN

result = df.groupby('Title')['Survived'].mean().sort_values(ascending=False)

result.head()`

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