ManideepTelukuntla
Passionate about ML and Data Science. MS in Business Analytics at UT Austin. Experienced Data Analyst, YouTube content creator, skilled in Python, Power BI, SQL
Austin, Texas, USA
Pinned Repositories
AB-Test-Insights-For-E-Commerce-Conversion
In this project, I will be working to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who “convert,” meaning the number of users who decide to pay for the company’s product. My goal is to work through the test results to help the company understand if they should implement this new page, keep the old page, or perhaps run the experiment longer to make their decision.
code_snippets
course-collaboration-travel-plans
DB-Dialogue
This project introduces a conversational chatbot capable of interpreting natural language queries, generating SQL queries accordingly, and fetching results from a SQL database. Leveraging GPT-4 for natural language processing and featuring a Streamlit GUI, it offers an intuitive and user-friendly interface for complex database interactions.
Digit-Classifier
Digit Classifier is a robust digit prediction system utilizing CNN & ViT models on the MNIST dataset, featuring a Flask backend on AWS ECS with Docker and an intuitive Anvil UI. Perfect for scalable, accurate digit recognition.
Marketing-Budget-Allocation-Optimization
This project utilizes Linear Programming to optimize marketing budget allocation across various channels, aiming to maximize Return on Investment (ROI) within organizational constraints.
Refining-Entry-Level-Luxury-Car-Strategies-With-Consumer-Insights
In this project, we analyzed Entry-Level Luxury Car Forum discussions. Using data scraping and Lift Analysis, we identified popular brand comparisons and attributes discussed. Further, we assessed consumer aspirations through brand mentions linked with aspiration-indicative words.
STA380-Part-II
In our "Introduction to Machine Learning" assignment, we have undertaken a comprehensive examination of the fundamental aspects of ML. This exploration spans the foundational principles of probability, advanced data wrangling techniques, the art of visual storytelling, methodologies in clustering and topic modeling, and the neural networks.
Stock-Portfolio-Optimization
This project focuses on optimizing a stock portfolio to track the NASDAQ-100 index using Integer Programming. Utilizing Gurobi, the approach involves selecting a subset of stocks and optimizing their weights to minimize tracking error.
Pneumonia_Detection_Using_Transfer_Learning
ManideepTelukuntla's Repositories
ManideepTelukuntla/Marketing-Budget-Allocation-Optimization
This project utilizes Linear Programming to optimize marketing budget allocation across various channels, aiming to maximize Return on Investment (ROI) within organizational constraints.
ManideepTelukuntla/STA380-Part-II
In our "Introduction to Machine Learning" assignment, we have undertaken a comprehensive examination of the fundamental aspects of ML. This exploration spans the foundational principles of probability, advanced data wrangling techniques, the art of visual storytelling, methodologies in clustering and topic modeling, and the neural networks.
ManideepTelukuntla/AB-Test-Insights-For-E-Commerce-Conversion
In this project, I will be working to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who “convert,” meaning the number of users who decide to pay for the company’s product. My goal is to work through the test results to help the company understand if they should implement this new page, keep the old page, or perhaps run the experiment longer to make their decision.
ManideepTelukuntla/code_snippets
ManideepTelukuntla/course-collaboration-travel-plans
ManideepTelukuntla/DB-Dialogue
This project introduces a conversational chatbot capable of interpreting natural language queries, generating SQL queries accordingly, and fetching results from a SQL database. Leveraging GPT-4 for natural language processing and featuring a Streamlit GUI, it offers an intuitive and user-friendly interface for complex database interactions.
ManideepTelukuntla/Digit-Classifier
Digit Classifier is a robust digit prediction system utilizing CNN & ViT models on the MNIST dataset, featuring a Flask backend on AWS ECS with Docker and an intuitive Anvil UI. Perfect for scalable, accurate digit recognition.
ManideepTelukuntla/Refining-Entry-Level-Luxury-Car-Strategies-With-Consumer-Insights
In this project, we analyzed Entry-Level Luxury Car Forum discussions. Using data scraping and Lift Analysis, we identified popular brand comparisons and attributes discussed. Further, we assessed consumer aspirations through brand mentions linked with aspiration-indicative words.
ManideepTelukuntla/Stock-Portfolio-Optimization
This project focuses on optimizing a stock portfolio to track the NASDAQ-100 index using Integer Programming. Utilizing Gurobi, the approach involves selecting a subset of stocks and optimizing their weights to minimize tracking error.
ManideepTelukuntla/course-git-blog-project
Sample repo of a blog for the Git course
ManideepTelukuntla/deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
ManideepTelukuntla/Demographic-Segmentation-For-Targeted-Marketing
In this project, I have worked with real-life data provided by Bertelsmann partners AZ Direct and Arvato Finance Solution. The data here concerns a company that performs mail-order sales in Germany. Their main question of interest is to identify facets of the population that are most likely to be purchasers of their products for a mail-out campaign.
ManideepTelukuntla/Exploring-Weather-Trends
In this project, I have analyzed local and global temperature data and compared the temperature trends where I live to overall global temperature trends.
ManideepTelukuntla/Feature-Selection-Using-MIQP-And-LASSO
This project explores feature selection in predictive analytics using Mixed Integer Quadratic Programming (MIQP) and LASSO (Least Absolute Shrinkage and Selection Operator). It aims to determine the effectiveness of these methods in selecting variables for regression models.
ManideepTelukuntla/Finding-Donors-For-CharityML
Finding donors for CharityML using supervised learning model
ManideepTelukuntla/FirstProject
Finding prime number
ManideepTelukuntla/Gradient-Descent-Algorithm
Gradient descent is used to bring down the error of model to minimum possible value
ManideepTelukuntla/Image-Classifier-Using-VGG16
This project classifies different species of flowers using deep learning models
ManideepTelukuntla/Investigate-TMDB-Movie-Data
This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue.
ManideepTelukuntla/lighthouse
Automated auditing, performance metrics, and best practices for the web.
ManideepTelukuntla/my-travel-plans
My travel plans
ManideepTelukuntla/Promo-Pulse
My team and I secured the second prize at the Dover Fueling Solutions Hackathon 2024. We developed an innovative multi-faceted solution designed to enhance customer experience, boost sales for convenience stores, and significantly accelerate the adoption of Anthem. Our approach utilizes dynamic advertising on the Anthem UI using machine learning.
ManideepTelukuntla/Ranges
Finding numbers in sequence and clubbing them into ranges
ManideepTelukuntla/STA380
STA 380: Predictive Modeling
ManideepTelukuntla/Time-Conversion
Converting time from 12hr format to 24hr format using C
ManideepTelukuntla/word_cloud
A little word cloud generator in Python