Hi, I'm Girish R, an aspiring Data Scientist with a passion for unraveling insights and
making data-driven decisions that drive business success.
My portfolio showcases a diverse range of data science projects, each a testament to my
expertise in collecting, analyzing, and visualizing data to derive meaningful conclusions.
Whether it's leveraging machine learning algorithms, conducting statistical analyses, or
designing interactive data dashboards, I thrive on turning raw data into actionable
insights.
I firmly believe that effective data science hinges on understanding business objectives
and user needs, crafting solutions that align with an organization's strategic goals.
I value working closely with stakeholders, subject matter experts, and fellow data
professionals to ensure that our projects are not only technically sound but also
aligned with real-world applications and goals. Committed to continuous learning and
staying at the forefront of data science tools, I thrive on taking on new challenges to
deliver impactful results.
Python - SQL - Statistical Analysis - ML - ML Frameworks - Tableau - Power BI - Excel
In the digital age, apps like Zomato thrive as platforms for users to share restaurant
reviews and experiences.
This paper includes an analysis of client ratings and reviews in
Zomato utilizing content mining. The Analysis solves some of the business cases that
can directly help the customers find the best restaurant in their locality and for
the company to grow up and work in the fields they are currently lagging in.
Consumers consider memory, display, battery, and camera when buying phones, often
lacking price validation resources, leading to suboptimal choices.
I've built a machine learning model using mobile phone features to categorize new
phones into price ranges (low, medium, high, very high). This empowers consumers to
make informed purchases, enhancing satisfaction and value for money.
In a saturated Google Play Store with over a million apps, the challenge for developers
and businesses is to discern the critical factors influencing user choices.
This
project aims to provide valuable insights into the app market and user preferences,
empowering developers to optimize their products based on data-driven decisions for
maximum impact.
To deliver impactful insights, I created a Power BI Sales Report focusing on best-selling products and customers. Constructed a dynamic data model using DAX for calculated columns and measures. The report's user experience was further enhanced through features like conditional formatting, drillthrough filters, and interactive visuals.
Project Link