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

Capstone project for Udacity's Intro to Machine Learning Course

Supervised learning based on census data to predict income to identify potential donors

This repository contains all the Machine Learning and Deep Learning projects that I worked on, spans across the two sub domains of Artificial Intelligence i.e., Computer Vision and Text Processing as a part of Machine Learning Nano Degree program at Udacity.

Machine Learning Notebooks

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

Apply unsupervised machine learning techniques on product spending data collected for customers of a wholesale distributor in Lisbon, Portugal to identify customer segments hidden in the data

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.

Data preprocessing methods explained with sample dataset

Machine Learning Engineer Nanodegree, Unsupervised Learning, Creating Customer Segments

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

Applied unsupervised learning techniques on demographic and spending data for a sample of German households.

Unsupervised Learning: Identify Target Customers

The objective of this project is to predication of bike rental count on daily based on the environmental and seasonal settings. As it gets easy for an organisation to arrange the resource if the demand spikes.

📏 Generic feature scaling methods

Using Machine Learning unsupervised learning techniques to see if any similarities exist between customers and use those similarities to segment customers into distinct categories using various clustering techniques

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

Machine Learning Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor