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

Hi there ๐Ÿ‘‹ I am Nitish Singh

About Me

As a Data Science YouTuber with over 150K+ subscribers, I am passionate about teaching others how to master Machine Learning, Deep Learning, Natural Language Processing, Computer Vision and Data Analysis. With over 100 repositories on GitHub, I am committed to sharing my knowledge and experience in these areas. My repositories include a wide range of projects, from simple examples to complex applications, all designed to help learners of all levels. With over 4.2k followers on GitHub, I am constantly engaged with the community, sharing insights and responding to questions. If you are interested in Data Science and looking to improve your skills, be sure to check out my repositories and YouTube channel.

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  • ๐Ÿ”ญ Iโ€™m currently working on Data Science Mentorship Program
  • ๐ŸŒฑ Iโ€™m currently learning SQL
  • ๐Ÿ‘ฏ Iโ€™m looking to collaborate on Deep Learning
  • ๐Ÿ’ฌ Ask me about Machine Learning, Deep Learning and NLP
  • ๐Ÿ“ซ How to reach me: [email protected]
  • ๐Ÿ˜„ Happy Learning

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

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()`

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.

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