duppala Goto Github PK

analyzing-visualizing-data-powerbi

This repository contains the lab files and other resources for the free Microsoft course DAT207x: Analyzing and Visualizing Data with Power BI. To learn how to connect, explore, and visualize data with Power BI, sign up for this course on edX.

customersegmentation

By means of this project I am trying to create a value-based customer segmentation model using RFM(Recency, Frequency, Monetary) analysis in python using pandas, numpy and matplotlib

data-analysis-python

Data analysis with Python and Jupyter

dbscan

A simple implementation of DBSCAN in Python

decision-tree-from-scratch

The purpose of this repository is to code a decision tree classifier from scratch using just numpy and pandas.

feature-selection-for-machine-learning

Methods with examples for Feature Selection during Pre-processing in Machine Learning.

google-adwords

kmeans_gui

Attempt on clustering using K means technique. Create a GUI to prompt the user to enter k number

logistic-regression-from-scratch

Building Logistic Regression from scratch

marketing-segmentation-rfm-analysis

pandas_exercises

Practice your pandas skills!

random-forest-classifier

A very simple Random Forest Classifier implementation in python.

random-forests

A basic random-forests algorithm written in python.

rfm_analysis

RFM (Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history – how recently, how often and how much did they buy. RFM helps divide customers into various categories or clusters to identify customers who are more likely to respond to promotions and also for future personalization services.

scikit-survival

Survival analysis built on top of scikit-learn

survival_analysis

Survival Analysis with non-parametric, semi-parametric, and parametric models

text-classification-models-tf

Tensorflow implementations of Text Classification Models.