A data preprocessing and feature engineering script for a machine learning pipeline is prepared.

Overview

FEATURE ENGINEERING

Business Problem: A data preprocessing and feature engineering script for a machine learning pipeline needs to be prepared. It is expected that the dataset will be ready for modelling when passed through this script.

Story of the Dataset:
The dataset is the dataset of the people who were in the Titanic shipwreck. It consists of 768 observations and 12 variables. The target variable is specified as "Survived";

0: indicates the person's inability to survive.

1: refers to the survival of the person.

ATTRIBUTES:

PassengerId: ID of the passenger

Survived: Survival status (0: not survived, 1: survived)

Pclass: Ticket class (1: 1st class (upper), 2: 2nd class (middle), 3: 3rd class(lower))

Name: Name of the passenger

Sex: Gender of the passenger (male, female)

Age: Age in years

Sibsp: Number of siblings/spouses aboard the Titanic
Sibling = Brother, sister, stepbrother, stepsister
Spouse = Husband, wife (mistresses and fiances were ignored)

Parch: Number of parents/children aboard the Titanic
Parent = Mother, father
Child = Daughter, son, stepdaughter, stepson
Some children travelled only with a nanny , therefore Parch = 0 for them.

Ticket: Ticket number # Fare: Passenger fare

Cabin: Cabin number

Embarked: Port of embarkation (C = Cherbourg, Q = Queenstown, S = Southampton)

REFERENCE: Data Science and ML Boot Camp, 2021, Veri Bilimi Okulu (https://www.veribilimiokulu.com/)

Owner
Pinar Oner
Data Science Enthusiast | Project Coordinator
Pinar Oner
A library to generate synthetic time series data by easy-to-use factors and generator

timeseries-generator This repository consists of a python packages that generates synthetic time series dataset in a generic way (under /timeseries_ge

Nike Inc. 87 Dec 20, 2022
Accelerating model creation and evaluation.

EmeraldML A machine learning library for streamlining the process of (1) cleaning and splitting data, (2) training, optimizing, and testing various mo

Yusuf 0 Dec 06, 2021
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour

Benedek Rozemberczki 619 Dec 14, 2022
BASTA: The BAyesian STellar Algorithm

BASTA: BAyesian STellar Algorithm Current stable version: v1.0 Important note: BASTA is developed for Python 3.8, but Python 3.7 should work as well.

BASTA team 16 Nov 15, 2022
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Benedek Rozemberczki 1.8k Jan 03, 2023
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

alkaline-ml 1.3k Dec 22, 2022
Winning solution for the Galaxy Challenge on Kaggle

Winning solution for the Galaxy Challenge on Kaggle

Sander Dieleman 483 Jan 02, 2023
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

Microsoft 8.4k Dec 30, 2022
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters.

TensorFlowOnSpark TensorFlowOnSpark brings scalable deep learning to Apache Hadoop and Apache Spark clusters. By combining salient features from the T

Yahoo 3.8k Jan 04, 2023
Kalman filter library

The kalman filter framework described here is an incredibly powerful tool for any optimization problem, but particularly for visual odometry, sensor fusion localization or SLAM.

comma.ai 276 Jan 01, 2023
Python package for stacking (machine learning technique)

vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa

Igor Ivanov 671 Dec 25, 2022
Used Logistic Regression, Random Forest, and XGBoost to predict the outcome of Search & Destroy games from the Call of Duty World League for the 2018 and 2019 seasons.

Call of Duty World League: Search & Destroy Outcome Predictions Growing up as an avid Call of Duty player, I was always curious about what factors led

Brett Vogelsang 2 Jan 18, 2022
distfit - Probability density fitting

Python package for probability density function fitting of univariate distributions of non-censored data

Erdogan Taskesen 187 Dec 30, 2022
Microsoft Machine Learning for Apache Spark

Microsoft Machine Learning for Apache Spark MMLSpark is an ecosystem of tools aimed towards expanding the distributed computing framework Apache Spark

Microsoft Azure 3.9k Dec 30, 2022
A Python package to preprocess time series

Disclaimer: This package is WIP. Do not take any APIs for granted. tspreprocess Time series can contain noise, may be sampled under a non fitting rate

Maximilian Christ 57 Dec 17, 2022
Machine learning that just works, for effortless production applications

Machine learning that just works, for effortless production applications

Elisha Yadgaran 16 Sep 02, 2022
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc)

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed

Chris Yuan 1 Feb 06, 2022
A simple python program that draws a tree for incrementing values using the Collatz Conjecture.

Collatz Conjecture A simple python program that draws a tree for incrementing values using the Collatz Conjecture. Values which can be edited: Length

davidgasinski 1 Oct 28, 2021
Fundamentals of Machine Learning

Fundamentals-of-Machine-Learning This repository introduces the basics of machine learning algorithms for preprocessing, regression and classification

Happy N. Monday 3 Feb 15, 2022
A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

A mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning.

Daniel Formoso 5.7k Dec 30, 2022