Shruti Goyal's repositories
CreditDefault-Evaluation-using-ANN
Project which will predict credit default or credit risk using artificial neural network algorithms. It will help banks and financial institutions to assign a credit score to the customer profile/portfolio and make a decision whether to sanction a loan or not
Aircraft-passenger-accomodation-ML-Model
The objective of this model is to write a python program for an airline to allocate seats to passengers when they make a booking. Seating configuration and number of bookings have been provided to us.
Credit-Analysis-Enhancement---Geospatial
Enhancing Credit analysis using Geospatial techniques. The predictive model is built on logistic regression and decision tree algorithms and produces an estimated default probability of the applicant. Models are built on normalised data to cover all possible scenarios from real life. The predictive probability will determine good and bad customers by classifying them into four categories. The output from predictive models is used on tableau to generate business dashboard. Models ability to classify and performance measurements were measured by using statistical metrics: Gini, KS and AUROC.
Airline-Seating-model-using-machine-learning
This project will allocate seat to a passenger based on their preferences and airplane requirements.
Machine-Learning-Credit-Scoring-Geospatial
Research work on credit scoring using geospatial data and techniques. This work presents interactive dashboard for enhancing credit analysis and assessment using GeoSpatial techniques for Irish residential properties de- veloped by data from following sources (i) loan portfolios and credit data (ii) property price register (iii) Central Statistical Office. These analyses can be used to reduce the chances of financial loss on a residential mortgage.
Classification
Classification is a data mining function that assigns items in a collection to target categories or classes. The goal of classification is to accurately predict the target class for each case in the data. For example, a classification model could be used to identify loan applicants as low, medium, or high credit risks.
Clustering
Clustering is the grouping of a particular set of objects based on their characteristics, aggregating them according to their similarities. Regarding to data mining, this metodology partitions the data implementing a specific join algorithm, most suitable for the desired information analysis. This project will work on K means clustering algorithm
Learning-Data-Mining-with-Python
Code repo for Learning Data Mining with Python, published by Packt Publishing
NSM_Assignment1
Dijistra's Algorithm
Predictive-Analytics-Projects
Contains collaboration projects on predictive analytics. Predictive analytics are used to determine customer responses or purchases, as well as promote cross-sell opportunities. Predictive models help businesses attract, retain and grow their most profitable customers. Improving operations.