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Saurabh Sindwani

Recently Published

Great Lakes | Simulation
Store's Take Away Design Selection using Simulation
Kaggle | Mercedes Benz
Clustering + Multiple Regression Models
Great Lakes | Forecasting Sales
Time Series using Decomposition, Holt Winters Modeling
Great Lakes | Churn Model
Logistic Regression, Step wise VIF reduction, Sensitivity vs Accuracy.
MIT | Integer Programming
1. Regression vs Optimization | Hotel Sites Selection 2. Sports Scheduling
MIT | Linear Programming
1. filatoi riuniti - optimize outsourcing strategies. 2. Gasoline Blending - Maximize profits, optimize mixing different crude oils to produce different products.
Kaggle | Instacart Market Basket Analysis | Solution
When managing memory is most important. # 32 million order products. XGBoost
Kaggle | Instacart Market Basket Analysis | EDA
EDA using ggplot2
Kaggle | House Prices
Kaggle | House Prices XGBoost, CV 10x20
Great Lakes | Employee Attrition Analysis - 2
Ensembling, Neural Net, Random Forest, CART, Hypothesis, EDA
Great Lakes | Employee Attrition Analysis
- CART - Tree Pruning - Inferences
Kaggle | Titanic Survival Analysis
Exploratory Analysis, Feature Engineering, Predictive Modeling using Random Forest Ensemble
Great Lakes | Regression Analysis - Addressing Multicollinearity
Regression Analysis - Detecting and addressing multicollinearity in case of correlated independent variables.
Great Lakes | Multivariate Regression Model - Use of Diagnostics
A multivariate regression model to predict the price of the Leslie Salt Land. Use of residual analysis and diagnostics to isolate influential observations.
Great Lakes | Factor Analysis - Cereal Data
Factor Analysis - Cereal Data - KMO & Bartlett Test - Parallel Analysis - Goodness of fit and residual statistics - Reliability of Factors - Characterization/Factorization of Variables
Johns Hopkins | Coursera | Machine Learning Project
Multi-Classification using Random Forests! In this project, we will use data from accelerometers(Jawbone Up, Nike FuelBand, and Fitbit) on the belt, forearm, arm, and dumbell of participants to predict the quality of the activity performed.
Johns Hopkins | Coursera | Regression Models Project
Exploratory Data Analysis; Statistical Confirmation; Model Building; Model Selection; Diagnostics
Johns Hopkins | Coursera | Developing Data Products - Assignment 3
A web application using R code deployed on the shiny server: https://saurabhsindwani.shinyapps.io/DataProducts/
Johns Hopkins | Coursera | Developing Data Products - Assignment 2
A web page presentation using R Markdown that features a plot created with Plotly.
Johns Hopkins | Coursera | Statistical Inference - Part 1
Central Limit Theorem! Investigate the distribution of averages of 40 exponentials over a 1000 simulations.
Johns Hopkins| Coursera | Reproducible Research Project
Exploratory Data Analysis! - Weather Data!
Johns Hopkins| Coursera | Data Products Assignment 1
Interactive maps using LEAFLET library.
Johns Hopkins | Coursera | Reproducible Research Assessment 1
Exploratory Data Analysis.