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

Overview

Feature-Engineering

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

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
kemalgunay
Ph.D | Data Science Researcher
kemalgunay
A Collection of Conference & School Notes in Machine Learning 🦄📝🎉

Machine Learning Conference & Summer School Notes. 🦄📝🎉

558 Dec 28, 2022
Simple structured learning framework for python

PyStruct PyStruct aims at being an easy-to-use structured learning and prediction library. Currently it implements only max-margin methods and a perce

pystruct 666 Jan 03, 2023
Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice

Responsible AI Workshop Responsible innovation is top of mind. As such, the tech industry as well as a growing number of organizations of all kinds in

Microsoft 9 Sep 14, 2022
2D fluid simulation implementation of Jos Stam paper on real-time fuild dynamics, including some suggested extensions.

Fluid Simulation Usage Download this repo and store it in your computer. Open a terminal and go to the root directory of this folder. Make sure you ha

Mariana Ávalos Arce 5 Dec 02, 2022
Napari sklearn decomposition

napari-sklearn-decomposition A simple plugin to use with napari This napari plug

1 Sep 01, 2022
Educational python for Neural Networks, written in pure Python/NumPy.

Educational python for Neural Networks, written in pure Python/NumPy.

127 Oct 27, 2022
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 Jan 06, 2023
A toolbox to iNNvestigate neural networks' predictions!

iNNvestigate neural networks! Table of contents Introduction Installation Usage and Examples More documentation Contributing Releases Introduction In

Maximilian Alber 1.1k Jan 05, 2023
Python package for causal inference using Bayesian structural time-series models.

Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI

Thomas Cassou 219 Dec 11, 2022
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

CatBoost 6.9k Jan 05, 2023
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker

Data Science on AWS - O'Reilly Book Get the book on Amazon.com Book Outline Quick Start Workshop (4-hours) In this quick start hands-on workshop, you

Data Science on AWS 2.8k Jan 03, 2023
A library of extension and helper modules for Python's data analysis and machine learning libraries.

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

Sebastian Raschka 4.2k Dec 29, 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
虚拟货币(BTC、ETH)炒币量化系统项目。在一版本的基础上加入了趋势判断

🎉 第二版本 🎉 (现货趋势网格) 介绍 在第一版本的基础上 趋势判断,不在固定点位开单,选择更优的开仓点位 优势: 🎉 简单易上手 安全(不用将api_secret告诉他人) 如何启动 修改app目录下的authorization文件

幸福村的码农 250 Jan 07, 2023
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in

Backprop 227 Dec 10, 2022
Lseng-iseng eksplor Machine Learning dengan menggunakan library Scikit-Learn

Kalo dengar istilah ML, biasanya rada ambigu. Soalnya punya beberapa kepanjangan, seperti Mobile Legend, Makan Lontong, Ma**ng L*v* dan lain-lain. Tapi pada repo ini membahas Machine Learning :)

Alfiyanto Kondolele 1 Apr 06, 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
Nevergrad - A gradient-free optimization platform

Nevergrad - A gradient-free optimization platform nevergrad is a Python 3.6+ library. It can be installed with: pip install nevergrad More installati

Meta Research 3.4k Jan 08, 2023
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
Price forecasting of SGB and IRFC Bonds and comparing there returns

Project_Bonds Project Title : Price forecasting of SGB and IRFC Bonds and comparing there returns. Introduction of the Project The 2008-09 global fina

Tishya S 1 Oct 28, 2021