Data Analyst | Machine Learning Engineer | Python Automation Engineer
Explore my projects and achievements on my
- 🔭 Currently working at Analogica Software Development Pvt Ltd as a Data Analyst & Python Automation Engineer.
- 🌱 Currently exploring advanced automation techniques.
- 👯 Open to collaborating on Data Analytics, Python Automation, and ETL Pipeline Development projects.
- 💬 Ask me about SQL, Python, Data Visualization, and Machine Learning.
- 📫 Reach me at: [email protected]
- Languages: Python, SQL, R
- Data Analysis: Exploratory Data Analysis (EDA), Statistical Analysis
- Visualization Tools: Power BI, Matplotlib, Seaborn, Matplotlib
- Automation: Python Automation, GUI (Tkinter), Email Automation (SMTP), Web Scraping (BeautifulSoup, Selenium)
- Database Management: SQL, MySQL, ETL Processes, Data Cleaning, PySpark
- Machine Learning: Supervised & Unsupervised Learning, Scikit-Learn
- Tools: Git, GitHub
- Bachelor of Engineering (Mechanical) – R L Jalappa Institute of Technology, Doddaballapur (2016–2020)
- PUC (PCMB) – Poorna Prajna P U College, Chickballapur (2014–2016)
- Tools Used: Python, Tkinter, Pandas, scikit-learn, Numpy, Flask, Render
- Developed a Flask-based web application that predicts the optimal crop to grow based on soil and weather conditions and recommends the right fertilizer for a healthier yield using a Random Forest Classifier.
- Implemented a machine learning model integrated with a Python backend and deployed the solution on Render Cloud.
- Planned future enhancements include integrating a real-time weather API for dynamic predictions, deploying on AWS SageMaker for scalability, and expanding to a mobile app version.
- Live App: agriculture-pridiction.onrender.com | GitHub Repo: github.com/1sumer/Agriculture_Pridiction.
- Tools Used: Python, MySQL, Tkinter, Pandas
- Developed a Python-based invoicing system that collects transaction data and stores it in MySQL for analysis.
- Automated invoice generation, improving accuracy and reducing manual errors by 30%.
- Performed customer behavior analysis to derive actionable insights for sales optimization.
- Tools Used: SQL, Python, Power BI, Pandas, NumPy
- Analyzed sales and shipping dynamics to improve profitability and operational efficiency.
- Built Power BI dashboards to identify trends, top-performing regions, and customer segments.
- Tools Used: Python (BeautifulSoup, Pandas), Power BI
- Scraped product data from e-commerce platforms to identify pricing trends and market positioning.
- Generated reports that informed competitive strategy formulation.
- The Importance of SQL in Today's World
- Python’s OOP Revolution
- Exploring the Core Principles of Decision Tree in Machine Learning
- Understanding Regularization: Preventing Overfitting
- Data Analytics with Python & SQL – Certisured
- Diploma in Machine Learning & AI – Certisured
- Scala Programming for Data Science – Scala
- Data Visualization: Empowering Business Insights – Tata Group
