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Day_15_Working_with_csv_Files.ipynb
Day_15_Working_with_csv_Files.ipynb
 
 
Day_16_Working_with_JSON_SQL.ipynb
Day_16_Working_with_JSON_SQL.ipynb
 
 
Day_17_Fetchhing_data_using_API.ipynb
Day_17_Fetchhing_data_using_API.ipynb
 
 
Day_18_Fetching_data_using_Web_Scraping.ipynb
Day_18_Fetching_data_using_Web_Scraping.ipynb
 
 
Day_19_Understand_ur_Data.ipynb
Day_19_Understand_ur_Data.ipynb
 
 
Day_20_EDA_using_Univariate_Analysis.ipynb
Day_20_EDA_using_Univariate_Analysis.ipynb
 
 
Day_21_EDA_using_Bivariate_and_Multivariate.ipynb
Day_21_EDA_using_Bivariate_and_Multivariate.ipynb
 
 
Day_22_Pandas_Profiling.ipynb
Day_22_Pandas_Profiling.ipynb
 
 
Day_24_Feature_Scaling_Standardization.ipynb
Day_24_Feature_Scaling_Standardization.ipynb
 
 
Day_25_Feature_Scaling_Normalization.ipynb
Day_25_Feature_Scaling_Normalization.ipynb
 
 
Day_26_Ordinal_Encoding_|_Encoding_Categorical_Data.ipynb
Day_26_Ordinal_Encoding_|_Encoding_Categorical_Data.ipynb
 
 
Day_27_One_Hot_Encoding_Handling_Categorical_Data.ipynb
Day_27_One_Hot_Encoding_Handling_Categorical_Data.ipynb
 
 
Day_28_Column_Transformer.ipynb
Day_28_Column_Transformer.ipynb
 
 
Day_29_Part_1_Titanic_Without_Using_Pipeline.ipynb
Day_29_Part_1_Titanic_Without_Using_Pipeline.ipynb
 
 
Day_29_Part_2_Titanic_Using_Pipeline.ipynb
Day_29_Part_2_Titanic_Using_Pipeline.ipynb
 
 
Day_30_Function_Transformer_[Log,Reciprocal,Square_Root].ipynb
Day_30_Function_Transformer_[Log,Reciprocal,Square_Root].ipynb
 
 
Day_31_Power_Transformer_[Box_Cox,_Yeo_Johnson].ipynb
Day_31_Power_Transformer_[Box_Cox,_Yeo_Johnson].ipynb
 
 
Day_32_Binning_and_Binarization.ipynb
Day_32_Binning_and_Binarization.ipynb
 
 
Day_32_Part_1_Binning.ipynb
Day_32_Part_1_Binning.ipynb
 
 
Day_33_Handling_Mixed_Variables.ipynb
Day_33_Handling_Mixed_Variables.ipynb
 
 
End_to_End_Toy_Project_|_Day_13.ipynb
End_to_End_Toy_Project_|_Day_13.ipynb
 
 
IPL Matches 2008-2020.csv
IPL Matches 2008-2020.csv
 
 
README.md
README.md
 
 
Social_Network_Ads.csv
Social_Network_Ads.csv
 
 
aug_train.csv
aug_train.csv
 
 
cars.csv
cars.csv
 
 
concrete_data.csv
concrete_data.csv
 
 
covid_toy.csv
covid_toy.csv
 
 
customer.csv
customer.csv
 
 
movie_titles_metadata.tsv
movie_titles_metadata.tsv
 
 
placement.csv
placement.csv
 
 
test.csv
test.csv
 
 
titanic.csv
titanic.csv
 
 
train.csv
train.csv
 
 
train.json
train.json
 
 
wine_data.csv
wine_data.csv
 
 
world.sql
world.sql
 
 
zomato.csv
zomato.csv
 
 

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Machine-Learning

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