Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

A Machine Learning Approach of Emotional Model

Karma of Humans is AI

This repository is a related to all about Machine Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python), Feature Selection technique in python etc. Follow Coursesteach for more content

Tutorial on how to perform feature encoding, feature scaling, and missing values imputation using the scikit-learn library

Exemplary, annotated machine learning pipeline for any tabular data problem.

This repository consist of a 50-day program. All the statistics required for the complete understanding of data science will be uploaded in this repository.

Creating Customer Segments - 4th project for Udacity's Machine Learning Nanodegree

Given dataset of Diamonds with features such as Cut, Carat, Clarity etc. I have used libraries such as Pandas, Numpy, Matplotlib, Seaborn to Analyse and Estimate the Price of Diamonds based on the features. Using Scikit-Learn , implemented Algorithms to increase the effective R2 score.

My solution to House-Prices Advanced Regression Techniques, A beginner-friendly project on Kaggle.

Machine learning algorithms repository

An attempt to predict the Stock Market Price using Long Short Term memory and plot its chart. By tweaking different hyper parameters, we get different trained models. The aim of this project is to identify the relation hidden in these hyper parameters.

Machine Learning Notebooks

The task is to build a machine learning regression model will predict the number of absent hours. As Employee absenteeism is a major problem faced by every employer which eventually lead to the backlogs, piling of the work, delay in deploying the project and can have a major effect on company finances. The aim of this project is to find an issue…

Machine-learning models to predict whether customers respond to a marketing campaign

Gradient Descent for N features using two datasets: Boston House data, Power Plant Data

Capstone project for Udacity's Intro to Machine Learning Course

Tariff is a list of expenses that incur while transporting the goods from one distance to another distance. Tariff is also dependent on seasonal and non-seasonal factors also. This project is aimed at predicting the tariff ratesfor truck load by using the different machine learning algorithms like lasso regression, elastic net regression, ridge …