Pranav Sagar

Hi, I am Software Engineer @ Glance - InMobi with a fervent passion for exploring the vast realms of technology. Experienced Software Engineer at Glance, specializing in Java, JavaScript, and Python. Silver Medalist in B.Tech Computer Science from Rajasthan Technical University. Active contributor to open-source projects and engaged in continuous learning and professional development. Recognized in national-level hackathons and coding competitions.

LinkedIn GitHub Resume

WORK EXPERIENCE

Software Engineer   at   Glance, inMobi                             Sept 2023 - present

Data Science Intern   at   Celebal Technologies                             May 2022 - July 2022

Skills: Data Science · SQL · Statistics · Machine Learning ·  Python · Artificial Neural Networks · EDA · Data Analysis

  • Delivered a Regression Model to help the client understand Carbon Dioxide Emission.
  • Assisted in predicting customers who are most likely subject to churn.
  • Performed EDA, Feature Engineering, and Clustering to analyze the target-specific market and improve customer satisfaction.
  • Developed a content-based recommendation system for movies by analyzing user behavior and historical data.
  • Trained the ANN model to improve the efficiency of the churn prediction model.


SKILLS

CERTIFICATIONS

Microsoft - Azure Data Fundamentals

Score: 871/1000

Microsoft - Azure AI Fundamentals

Microsoft - Azure AI Fundamentals

Score: 857/1000

Databricks - Fundamentals of the Databricks Lakehouse

Databricks - Fundamentals of the Databricks Lakehouse

GitHub Hacktoberfest 2022

GitHub Hacktoberfest 2022

Contributed to 4 open-source projects

NPTEL

NPTEL

IT Kharagpur - Programming in Java
Score: 73%

PROJECTS

Movie-Recommendation-System

Machine learning, content-based filtering, Natural language processing (NLP),  Streamlit
Created a content-based recommendation system for the TMDB Movies dataset utilizing advanced filtering techniques. This recommendation engine analyses the content of movies, such as genre, director, actors, etc., to generate personalized suggestions for users based on their movie preferences. The engine was developed to provide users with relevant and targeted recommendations, enhancing their movie-watching experience.

Github
Amazon Review Sentiments

NLP, Classification, Machine Learning
The objective of this project is to analyse customer sentiment towards various products through the analysis of product reviews. The sentiment analysis will be performed using Natural Language Processing (NLP) techniques and machine learning algorithms

Github
House Pricing Prediction with Flask deployment

Flask, Linear Regression, Machine Learning
This project provides an end-to-end solution for clients who are interested in predicting the cost of a house. The project has a user-friendly interface that allows the client to input their requirements and receive an accurate prediction of the house price.

Github
Tic Tac Toe

Python, Tkinter 
Tic Tac Toe game created in Python with GUI where two players mark X's and O's on a 3x3 grid until one player gets three in a row or all spaces are filled

Github
Event Management System

Machine learning, content-based filtering, Natural language processing (NLP),  Streamlit
Developed Java GUI application for Event management with the feature of retrieving and displaying data from SQLite database using Swing framework.

Github
Sales Report / Dashboard

Microsoft Power BI
Created a sales report using Power BI to analyze the performance of the Product sales and identify product sales.

view

COURSES

ACHIEVEMENTS & ACTIVITIES

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