This jupyter notebook project was completed by me and my friend using the dataset from Kaggle

Overview

ARM

This jupyter notebook project was completed by me and my friend using the dataset from Kaggle.

The world Happiness 2017, which ranks 155 countries by their Happiness Levels was released at the UN
at an event celebrating International Day of Happiness on March 20th. The dataset in this lists happiness levels of people in those 155 countries.

We are using Association Rule Mining to find out what factor or feature is the most important in deciding the happiness levels.

The following shows the steps carried out in the Jupyter notebook:

  • The Jupyter notebook starts by reading the csv file
  • Data Cleaning
  • Making Histogram and Box Plots
  • Testing for Redundancies using Chi-Square Test
  • Checks Correlation between attributes
  • Dimensionality Reduction using PCA
  • Generating Features by first dividing data into two categories
  • Generating and Analyzing rules using Apriori
Data from "Datamodels: Predicting Predictions with Training Data"

Data from "Datamodels: Predicting Predictions with Training Data" Here we provid

Madry Lab 51 Dec 09, 2022
hgboost - Hyperoptimized Gradient Boosting

hgboost is short for Hyperoptimized Gradient Boosting and is a python package for hyperparameter optimization for xgboost, catboost and lightboost using cross-validation, and evaluating the results o

Erdogan Taskesen 34 Jan 03, 2023
Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)

Short PhD seminar on Machine Learning Security (Adversarial Machine Learning)

141 Dec 27, 2022
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

Spark Python Notebooks This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, fro

Jose A Dianes 1.5k Jan 02, 2023
Machine Learning e Data Science com Python

Machine Learning e Data Science com Python Arquivos do curso de Data Science e Machine Learning com Python na Udemy, cliqe aqui para acessá-lo. O prin

Renan Barbosa 1 Jan 27, 2022
Firebase + Cloudrun + Machine learning

A simple end to end consumer lending decision engine powered by Google Cloud Platform (firebase hosting and cloudrun)

Emmanuel Ogunwede 8 Aug 16, 2022
Bayesian Additive Regression Trees For Python

BartPy Introduction BartPy is a pure python implementation of the Bayesian additive regressions trees model of Chipman et al [1]. Reasons to use BART

187 Dec 16, 2022
Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.

Linear Models Implementations of LinearRegression, LassoRegression and RidgeRegression with appropriate Regularizers and Optimizers. Linear Regression

Keivan Ipchi Hagh 1 Nov 22, 2021
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
Send rockets to Mars with artificial intelligence(Genetic algorithm) in python.

Send Rockets To Mars With AI Send rockets to Mars with artificial intelligence(Genetic algorithm) in python. Tools Python 3 EasyDraw How to Play Insta

Mohammad Dori 3 Jul 15, 2022
A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and motion planning

pybullet-planning (previously ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and

Caelan Garrett 260 Dec 27, 2022
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class

Tamas Madl 482 Nov 19, 2022
Pyomo is an object-oriented algebraic modeling language in Python for structured optimization problems.

Pyomo is a Python-based open-source software package that supports a diverse set of optimization capabilities for formulating and analyzing optimization models. Pyomo can be used to define symbolic p

Pyomo 1.4k Dec 28, 2022
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

2 Jun 14, 2022
Machine Learning University: Accelerated Natural Language Processing Class

Machine Learning University: Accelerated Natural Language Processing Class This repository contains slides, notebooks and datasets for the Machine Lea

AWS Samples 2k Jan 01, 2023
Generate music from midi files using BPE and markov model

Generate music from midi files using BPE and markov model

Aditya Khadilkar 37 Oct 24, 2022
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft 366 Jan 03, 2023
CobraML: Completely Customizable A python ML library designed to give the end user full control

CobraML: Completely Customizable What is it? CobraML is a python library built on both numpy and numba. Unlike other ML libraries CobraML gives the us

Sriram Govindan 14 Dec 19, 2021
Predicting job salaries from ads - a Kaggle competition

Predicting job salaries from ads - a Kaggle competition

Zygmunt Zając 57 Oct 23, 2020