A showcase of my work and skills
Hello! I'm Gangadhar, a highly motivated individual with a Bachelor of Technology in Electronics and Communication from the National Institute of Technology. I possess a robust foundation in data analysis, machine learning, and deep learning, with hands-on experience in various domains including hardware, networking, and data visualization.
I have developed strong skills in programming languages such as Python and SQL, and I am proficient in tools like Jupyter Notebook, VS Code, and Power BI. My certifications in Data Science, Database Management, Python, and MySQL from platforms like NPTEL and HackerRank further validate my technical prowess.
My recent projects highlight my capabilities in data analysis and software development. These include conducting an Exploratory Data Analysis (EDA) on sales data to identify key trends and insights, developing a comprehensive Bank Management System, and creating a Facial Emotion Detection system using convolutional neural networks (CNN). I am passionate about applying my analytical skills to derive meaningful insights and solutions that drive business growth.
– Conducted an Exploratory Data Analysis (EDA) on a comprehensive sales dataset, focusing on identifying key sales trends, top-performing products, and valuable customers. – Utilized Python and popular data analysis libraries such as Pandas, Matplotlib, and Seaborn to clean, visualize, and analyze the data. – Generated actionable insights and recommendations to enhance sales strategies and improve business performance.
View Project– Designed and developed a comprehensive Bank Management System using Python and SQL, offering functionalities for managing customer accounts, transactions, and loans. – Implemented a secure login system with different user roles (admin and customer) to ensure data privacy and access control. – Conducted rigorous testing and debugging to ensure system reliability, performance, and security.
View Project– Developed a Facial Emotion Detection system using convolutional neural networks (CNN) to accurately identify and classify emotions from facial expressions. – Preprocessed and augmented a large dataset of facial images to improve model accuracy and robustness. – Employed deep learning frameworks such as TensorFlow and Keras to build, train, and evaluate the CNN model. – Achieved high accuracy in emotion classification, providing valuable insights for applications in user experience, security, and psychological research.
View Project– Created an interactive report to visualize sales data, enabling dynamic analysis and insights into sales performance and trends. – Designed user-friendly visualizations including bar charts, line graphs, tables and donut chart, providing a comprehensive view of sales metrics and regional performance.
View ProjectPython
SQL
Pandas
Numpy
Matplotlib
Plotly
Scipy
Seaborn
Data Visualization
MS Excel
Power BI
Machine Learning
Deep Learning
Statistics
Git