This Portfolio is a compilation of all the Data Science and Data Analysis projects I have done for academic, self-learning and hobby purposes. This portfolio also contains my Achievements, skills, and certificates. It is updated on a regular basis.
- Email: eastariuday123@gmail.com
- LinkedIn: linkedin.com/UdaykiranEstari
- Tableau: tableau.com/UdaykiranEstari
- Recipient of Best Student Award for Outstanding overall performance by securing 9.5 SGPA in 5 Consecutive semesters.
- Recipient of FFE Scholarship and Fee Waiver for excellent academic performance (98.5%).
- Winner of the 61st National SGFI Competition, securing first place in the Individual and Team championship categories.
Real-time CO2 Emissions Forecasting with Time Series Models
In this project, I have extracted data of real-time CO2 emissions using an API, cleaned and preprocessed the data, and built various time series models including AR, ARIMA, SARIMA, and LSTM. The repository also includes the necessary scripts for analyzing the models and selecting the best-performing ones. Finally, the selected model is used for forecasting CO2 emissions for the next 10 years.
COVID-19 UK Tracker: Interactive Graphical User Interface
In this Project, I developed a COVID-19 UK Cases GUI using Tkinter in Python. It offers real-time data updates, interactive graphs, date selection via a calendar widget, and a convenient place comparison feature. This user-friendly interface provides up-to-date COVID-19 information, interactive visuals, and the ability to focus on specific dates or regions for analysis.
Unlocking App Success: A Data-Driven Journey with SQL on Apple Store Apps
I leveraged SQL to uncover valuable insights for app developers. From the advantages of paid apps and language support optimization to pinpointing lower-rated app categories, Examined the role of app descriptions in user ratings and provided a benchmark for new apps looking to stand out in a competitive market. I addressed the competitive games and entertainment genres, revealing a path to success through unique value and quality.
AdOptimize: Instagram A/B Testing for Sales and Traffic Boost
This Git repository focuses on A/B testing of Instagram ad campaigns to optimize sales and drive traffic. The goal is to maximize the effectiveness of your advertising efforts on Instagram by experimenting with different variations and strategies.
- Methodologies: Machine Learning, Deep Learning, Time Series Analysis, Natural Language Processing, Statistics, A/B Testing and Experimentation Design, Big Data Analytics
- Languages: Python (Pandas, Numpy, Scikit-Learn, Scipy, Keras, Matplotlib), R (Dplyr, Tidyr, Caret, Ggplot2), SQL
- Tools: MySQL, Tableau, Git, PySpark, Amazon Web Services (AWS), Flask, MS Excel
