The functions we created are included in a script. The necessary parts for pre-processing were taken. Analysis complete.

Overview

Feature-Engineering

The functions we created are included in a script. The necessary parts for pre-processing were taken. Analysis complete.

image

Business Problem

/Required for a machine learning pipeline data preprocessing and variable engineering script needs to be prepared.

/When the dataset is passed through this script, the modeling starts. Expected to be ready.

Dataset Story

*The data set is the data set of the people who were in the Titanic shipwreck. *It consists of 768 observations and 12 variables.

The target variable is specified as "Survived";

1: one's survival, 0: indicates the person's inability to survive.

Variables

  • Survived

  • 0 Died, 1 Survived

  • Pclass – Ticket Class

  • 1 = Grade 1, 2 = Grade 2, 3 = Grade 3

  • Age – Age

  • Sibsp – Number of siblings / spouses on the Titanic

  • Sex – Gender

  • Parch – Number of parents/children on Titanic

  • Embarked: – Passenger embarkation port

  • (C = Cherbourg, Q = Queenstown, S = Southampton

  • Fare – Ticket fare

  • Cabin: Cabin number

Project Tasks

1- Open a directory called helpers in the working directory and enter it. Add a script named data_prep.py. In the Feature Engineering section, all of our own collect functions into this script. Functions that should be here: outlier_thresholds replace_with_thresholds check_outlier grab_outliers remove_outlier missing_values_table missing_vs_target label_encoder one_hot_encoder rare_analyser rare_encoder

2- Write a function called titanic_data_prep. Data preprocessing or EDA functions required for this function, Get it from the eda.py and data_prep.py files in the helpers.

3- Save the data set you preprocessed to the disk with pickle.

Owner
Ayşe Nur Türkaslan
I continue my studies in the field of Data Science and Artificial Intelligence. I want to turn my efforts into a contribution using Github
Ayşe Nur Türkaslan
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