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
Covid-polygraph - a set of Machine Learning-driven fact-checking tools

Covid-polygraph, a set of Machine Learning-driven fact-checking tools that aim to address the issue of misleading information related to COVID-19.

1 Apr 22, 2022
决策树分类与回归模型的实现和可视化

DecisionTree 决策树分类与回归模型,以及可视化 DecisionTree ID3 C4.5 CART 分类 回归 决策树绘制 分类树 回归树 调参 剪枝 ID3 ID3决策树是最朴素的决策树分类器: 无剪枝 只支持离散属性 采用信息增益准则 在data.py中,我们记录了一个小的西瓜数据

Welt Xing 10 Oct 22, 2022
#30DaysOfStreamlit is a 30-day social challenge for you to build and deploy Streamlit apps.

30 Days Of Streamlit 🎈 This is the official repo of #30DaysOfStreamlit — a 30-day social challenge for you to learn, build and deploy Streamlit apps.

Streamlit 53 Jan 02, 2023
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

23.3k Dec 31, 2022
Transform ML models into a native code with zero dependencies

m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code

Bayes' Witnesses 2.3k Jan 03, 2023
cuML - RAPIDS Machine Learning Library

cuML - GPU Machine Learning Algorithms cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions t

RAPIDS 3.1k Dec 28, 2022
A Tools that help Data Scientists and ML engineers train and deploy ML models.

Domino Research This repo contains projects under active development by the Domino R&D team. We build tools that help Data Scientists and ML engineers

Domino Data Lab 73 Oct 17, 2022
Open MLOps - A Production-focused Open-Source Machine Learning Framework

Open MLOps - A Production-focused Open-Source Machine Learning Framework Open MLOps is a set of open-source tools carefully chosen to ease user experi

Data Revenue 590 Dec 28, 2022
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco

Christoph Mark 129 Dec 24, 2022
Scikit-Learn useful pre-defined Pipelines Hub

Scikit-Pipes Scikit-Learn useful pre-defined Pipelines Hub Usage: Install scikit-pipes It's advised to install sklearn-genetic using a virtual env, in

Rodrigo Arenas 1 Apr 26, 2022
Iterative stochastic gradient descent (SGD) linear regressor with regularization

SGD-Linear-Regressor Iterative stochastic gradient descent (SGD) linear regressor with regularization Dataset: Kaggle “Graduate Admission 2” https://w

Zechen Ma 1 Oct 29, 2021
SPCL 48 Dec 12, 2022
This repository has datasets containing information of Uber pickups in NYC from April 2014 to September 2014 and January to June 2015. data Analysis , virtualization and some insights are gathered here

uber-pickups-analysis Data Source: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city Information about data set The dataset contain

B DEVA DEEKSHITH 1 Nov 03, 2021
A chain of stores, 10 different stores and 50 different requests a 3-month demand forecast for its product.

Demand-Forecasting Business Problem A chain of stores, 10 different stores and 50 different requests a 3-month demand forecast for its product.

Ayşe Nur Türkaslan 3 Mar 06, 2022
A Pythonic framework for threat modeling

pytm: A Pythonic framework for threat modeling Introduction Traditional threat modeling too often comes late to the party, or sometimes not at all. In

Izar Tarandach 644 Dec 20, 2022
MLFlow in a Dockercontainer based on Azurite and Postgres

mlflow-azurite-postgres docker This is a MLFLow image which works with a postgres DB and a local Azure Blob Storage Instance (Azurite). This image is

2 May 29, 2022
This repository contains the code to predict house price using Linear Regression Method

House-Price-Prediction-Using-Linear-Regression The dataset I used for this personal project is from Kaggle uploaded by aariyan panchal. Link of Datase

0 Jan 28, 2022
The easy way to combine mlflow, hydra and optuna into one machine learning pipeline.

mlflow_hydra_optuna_the_easy_way The easy way to combine mlflow, hydra and optuna into one machine learning pipeline. Objective TODO Usage 1. build do

shibuiwilliam 9 Sep 09, 2022
This repo includes some graph-based CTR prediction models and other representative baselines.

Graph-based CTR prediction This is a repository designed for graph-based CTR prediction methods, it includes our graph-based CTR prediction methods: F

Big Data and Multi-modal Computing Group, CRIPAC 47 Dec 30, 2022
Metric learning algorithms in Python

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

1.3k Dec 28, 2022