• 🌱 At Epython Lab, we specialize in providing Data Engineering, Data Science, and Web Development solutions.
• 💼 Our team is passionate about analyzing datasets, uncovering insights, and developing strategies to help businesses grow.
• 🚀 We have expertise in Python, SQL, Flask, Streamlit, Power BI, Tableau, and Teaching.
• 📚 We are committed to continuous learning and innovation, expanding our capabilities in machine learning, data visualization, and web technologies.

Programming Languages & Frameworks	Data Visualization & Analytics	Cloud & DevOps	Web Development	IDEs & Editors

Description: A machine learning model developed to predict credit risk and assign credit scores, supporting data-driven lending decisions for Bati Bank's Buy-Now-Pay-Later (BNPL) service in collaboration with an eCommerce platform.

Tools Used: Python, Flask, Sklearn, Visualization Tools

Key Features:

• Exploratory Analysis
• RFM Model Development(Customer Risk Classification)
• Machine Learn Model(Predicting Customer Risk)
• Report

Description: Building a real-time data ingestion and entity extraction pipeline for Amharic messages from Ethiopian e-commerce Telegram channels. The system leverages fine-tuned Large Language Models (LLMs) to identify key business entities such as product names, prices, and locations. The extracted information is used to populate a centralized platform for EthioMart, aiming to streamline e-commerce activities in Ethiopia by consolidating decentralized Telegram channels into a unified hub. The project also includes handling Amharic-specific linguistic features and evaluating model performance for Named Entity Recognition (NER).

Tools Used: Python, Flask, Sklearn, Visualization Tools, Deep Learning

Key Features:

• Extract Amharic Telegram Messages(E-commerce channels)
• Labeling the extracting messages(NER)
• Train the model using Deep Learning(LLM)
• Report)

Description: This project mainly focused on predictive analytics for business. In this project repo, there are 6 different predictive projects you can explore each of them.

Tools Used: Python, Tableau, Alteryx.

Description: This project mainly focused on the GitHub Search Tool, which provides enhanced search functionality and allows users to find repositories based on topics, ratings, and programming languages.

Tools Used: Python, Flask. Key Features:

• Search top-rated GitHub repo
• Search by programming
• Search by Topic

Description: The project is designed to enhance stock market predictions by combining quantitative and qualitative data.

Tools Used: Python, Matplotlib, NLP, etc.
Key Features:

• Sentiment Analysis
• Correlation Analysis
• Financial Quantitative Analysis Project Report

Description: A machine learning solution to forecast sales for Rossmann Pharmaceuticals' stores across various cities six weeks in advance. Factors like promotions, competition, holidays, seasonality, and locality are considered for accurate predictions. The project structure is organized to support reproducible and scalable data processing, modeling, and visualization.

Tools Used: Python, Matplotlib, Seaborn, Tensorflow Scikitlearn, etc.
Key Features:

• Customer Behavior Analysis(EDA)
• Data Preprocessing(Feature Engineering)
• Sales Prediction(RandomForestRegressor)
• Sales Forecasting using a Deep Learning Model Project Report

Description: A project analyzing car insurance claims data to optimize premiums and marketing strategies.

Tools Used: Python, Matplotlib, Seaborn, sci-kit-learn,scipy, shap etc.
Key Features:

• Statistical modeling using Machine Learning Models
• A/B hypothesis testing
• Visualization Project Report

Description: focused on comprehensively analyzing user behavior, engagement, experience, and satisfaction in a telecom dataset.

Tools Used: Python, Matplotlib, sci-kit-learn, etc.
Key Features:

• User Overview Analysis: Analyze handset usage, manufacturers, and application usage.
• User Engagement Analysis: Track engagement across different applications and cluster users based on engagement metrics.
• Experience Analytics: Assess user experience based on network parameters and device characteristics.
• Satisfaction Analysis: Calculate and predict user satisfaction scores based on engagement and experience. Project Report

• 📊 Data-Driven Decisions: We help businesses leverage their data to make smarter decisions.
• 💡 Innovation: We constantly explore new technologies and methodologies to provide cutting-edge solutions.
• 🤝 Collaboration: Our work culture thrives on collaboration with clients and partners to ensure the best outcomes.

At Epython Lab, we are always open to new opportunities and partnerships. Contact us for collaboration, consulting, or any data-driven project needs!