Predicting Survival in Titanic!

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Part — 1 : Data Cleaning

Getting Started

datasets being imported through Jupyter notebook
shape of imported datasets as shown in jupyter notebook
first 5 rows in the training dataset
the output has 0 and 1 as only unique value
code to combine the two datasets
code for checking NULL values in the combined dataset

Feature Engineering and EDA

adding the list as a new column and checking the output
distribution between male and female
information on the continuous variable Age
filling missing Age values for Females
filling missing Age values for Males
Scaling the Fare column plotting the output
  1. Data import
  2. Data merging
  3. Individual Feature Study
  4. Feature Engineering
  5. Feature Transformation

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Project Manager with 11 years of industry experience. Data Science enthusiast. Entrepreneur.

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Aditya Vyas

Aditya Vyas

Project Manager with 11 years of industry experience. Data Science enthusiast. Entrepreneur.

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