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SRUTHI REDDY NARAPAREDDY

An avid programmer who is passionate about providing data driven business decisions and building Machine Learning solutions. Software Engineer with about 6 years of experience in ML/AI and Software Development. Currently, working as an Artificial Intelligence Engineer with Centific (Formerly PacteraEdge) building AI and analytics platforms to interesting and challenging use cases in multiple industries.

During my Masters in Business Analytics at UIC, I have interned with Cresco Labs and designed solution to forecast the demand for sales and quantified the effect of different factors on the demand. Also as a Data analyst at UIC, built data pipelines, Ad-hoc reports, EDA and interactive Tableau dashboards for data visualizations to drive business decisions

Prior to my masters, I have worked as an application developer with Oracle Corp building backend solution, UI, API, DB queries for the banking product.

Highly skilled in SQL, Python, Statistics, Data Visualization, Computer vision, NLP, Predictive analytics, Statistics, Tableau, ETL, R, A/B Testing.

Personal Interests: Dance, painting, Sudoku

Education

Masters in Business Analytics, 2020

University of Illinois, Chicago

B.E in Chemical Engineering, 2016

BITS PILANI, Hyderabad

Coursework

Data Mining
Machine Learning
Advanced Database Management
Advanced Predictive Modelling
Business Data Visualization
Advanced Text Analytics
Operations Management
Revenue Management

Interests

Data Science
Data Visualization
Deep Learning
Statistics
Generative AI / LLMs

Who are we

Skills

skills

Certifications

How it works

Projects

The Wizarding world of Harry Potter

February 2021

Deployed a flask application on cloud using AWS EBS. Go find the skills of your favorite character in Harry potter in the live application here

video

Python, AWS,
Flask, HTML,CSS

Image Captioning

Spring 2020

Generated textual descriptions for images using CNN -LSTM as encoder and decoder by implementing Transfer learning through Resnet 152 pre trained model and analyzed the results using BLEU 3, 4 metrics.

Github

Pytorch,
CNN, LSTM

Sentiment Analysis

Fall 2019

Performed sentiment analysis on Amazon Twitter data using TF-IDF and logistic regression in python (Sci-kit Learn) and achieved a 70% accuracy with 88.6% recall

Github

NLP, Pyspark,
Logistic Regression

Netflix Content Analysis

Summer 2020

Transformed the Netflix content data using Alteryx and performed exploratory data analysis by creating visualizations in Tableau.

Tableau Public

Tableau, Alteryx

Recommendation System

Spring 2020

Built a movie recommendation system using Alternating least squares optimizer with Matrix factorization algorithm using Python with 0.912 RMSE

Github

Pyspark,
ALS,
Matrix Factorization

Analysis of Airline On-Time Flight Performance

Fall 2019

Created an interactive Tableau dashboard which highlighted the key features of Envoy airlines and compared delay performance with their competitor and provided recommendations to increase their on-time performance

Tableau public

Tableau

Customer Engagement Analysis

Spring 2020

• Built a classification model to predict customer behavior using ensemble techniques such as Random forest (RF) and XGBoost (on imbalanced data) with 98.9% recall
• Performed feature selection from 700 columns using RF and LASSO after applying SMOTE to balance the data

Github

R, ggplot2,
SMOTE, XGBOOST,

RF, Ridge & Lasso Regression

Image Classification

Spring 2020

Predicted the different classes of images in CIFAR dataset with an accuracy of 92% using deep CNN (Pytorch) architectures and the hand drawn digits of MNIST dataset with 97.24% (Keras)

Github

Pytorch, Keras,

CNN

Prediction of Net Promoter Score- Manipal Hospitals

Fall 2019

Developed Random forest and Adaboost models to predict NPS scores. Analyzed the impact of oversampling and undersampling on the prediction accuracy of both the models. Achieved higher accuracy of 74.5% with oversampled data.

Github

R, Random forest,
Stepwise Regression,
Adaboost

experience