Shoaib's repositories
Unsupervised-Learning
5 Projects based on Unsupervised learning
Semiconductor-manufacturing-process
Build a classifier to predict the Pass/Fail yield of a particular process entity and analyse whether all the features are required to build the model or not.
Creation-of-an-India-Credit-Risk-Default-Model
The project involved developing a credit risk default model using a given data which had to be checked for outliers, missing values, multicollinearity etc. Univariate and Bivariate Analysis had to be conducted and the model had to be built using Logistic Regression on most important variables. Model Performance Measures were undertaken that included predicting the accuracy of the model on certain datasets.
Diagnosing-Parkinsons-disease
Goal is to classify the patients into the respective labels ( Healthy/ Parkinson) using the attributes from their voice recordings
Online-Retail-Data-Analysis
This Online Retail data set contains all the transactions occurring for a UK-based and registered, non-store online retail between 01/12/2009 and 09/12/2011.
Taiwan-Credit-Card-Default
A data set of 30000 records and 24 variables containing information on defaults, demographic factors, credit data, delinquency, repayment and billed amounts of a credit card client in Taiwan from April 2005 to September 2005. The objective was to apply statistical, data visualization and Machine learning techniques (supervised and unsupervised) on the data set to come up with insights and recommendations that could have been used to control bad debts.
Bangalore-Housing-Price-Prediction
The objective of the project is to create a machine learning model. We are doing a supervised learning and our aim is to do predictive analysis to predict housing price.
Building-a-supervised-Model-to-cross-sell-personal-loans
The objective of this exercise was to build a model using a Supervised learning technique to figure out profitable segments to target for cross-selling personal loans. A Pilot campaign data of 20000 customers was used which included several demographic and behavioral variables. The Model was further validated and a deployment strategy was recommended.
Built-a-forecasting-model-to-predict-monthly-gas-production
The project involved developing an ARIMA model to forecast the monthly Australian gas production level for the next 12 months.
California-Housing-Price-Prediction
The objective of the project is to create a machine learning model. We are doing a supervised learning and our aim is to do predictive analysis to predict median housing price.
Cell-Phone-Churn
The primary objective was to investigate the parameters contributing for customer churn (attrition) in the Telecom Industry. A Logistic Regression Model was developed and validated with test data to predict customer churn.
Choosing-preferable-mode-of-transport-by-employees
The project involves deciding on the mode of transport that the employees prefer while commuting to office. For this, multiple models such as KNN, Naive Bayes, Logistic Regression have been created and explored to check their model performance metrics. Bagging and Boosting modelling procedures have also been applied to create the models.
Credit-Card-Fraud-Detection
It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. Here, the aim is to analyze the dataset and detect the fradulent transactions.
Customer-flight-satisfaction-prediction
The data at hand is of flight satisfaction survey along with the customer flight information, the task at hand is to build a model that predicts satisfaction/dissatisfaction given the various attributes
Customer-Satisfaction-Hair-product
The objective of the project is to use the dataset to build a regression model to predict satisfaction. Project Approach, Data Exploration, Collinearity of the variables ,Initial Regression analysis Factor Analysis, Labeling and interpreting of the factors, Regression analysis using the factors as independent variable, Model performance measures
EDA-Auto-Honey-
This dataset consist of data From 1985 Ward's Automotive Yearbook Honey production data was published by the National Agricultural Statistics Service (NASS) of the U.S. Department of Agriculture.
EDA-Telecom-churn-
This 2018 Developer Survey results are organized on Kaggle in two tables and Telecom churn dataset on Kaggle, objective was EDA
EDA-uberdrive
The data of a driver’s uber trips are available for year 2016. Your manager wants you to explore this data to give him some useful insights about the trip behaviour of a Uber driver.The dataset contains Start Date, End Date, Start Location, End Location, Miles Driven and Purpose of drive (Business, Personal, Meals, Errands, Meetings, Customer Support etc.)
Evaluated-the-impact-of-a-new-golf-ball-coating
This project used Hypothesis Testing and visualization to evaluate a new golf ball coating designed to resist cuts and provide durability by comparing the driving distances of the old and new golf ball.
Health-Insurance
This project used Hypothesis Testing and Visualization to leverage customer's health information like smoking habits, bmi, age, and gender for checking statistical evidence to make valuable decisions of insurance business like charges for health insurance.
Identifying-potential-customers-for-loans
Identified potential loan customers for Thera Bank using classification techniques. Compared models built with Logistic Regression and KNN algorithm in order to select the best performing one.
Pitch-Analysis-of-Shark-Tank-contestants
Initial text mining exercise was performed on a dataset of Shark tank episodes with 495 entrepreneurs making their pitch to VCs. Used that to build multiple models (CART, Random Forest, Logistic Regression) to predict keywords which have an impact on striking a deal.
Recommending-ways-to-increase-revenue-of-a-Coffee-Chain
The project involves conducting a thorough analysis of Point of Sale (POS) Data for providing recommendations through which a coffee chain restaurant can increase its revenue by either taking off certain items from the menu or coming up with popular combo meals for customers.
TSF-Internship
These are the tasks that were assigned during the one month internship.