You will get Classifying 28,000 Songs in Real-Time — Spark MLlib NLP Pipeline
Project details
You will get a complete, production-ready machine learning solution tailored to your business problem — not just a model, but a clear, explainable, and deployable ML system.
I specialize in building end-to-end ML pipelines covering data preprocessing, feature engineering, model selection, hyperparameter tuning, and performance evaluation. Every project is approached with a strong focus on accuracy, reliability, and real-world usability.
Unlike generic models, I take time to understand your data and objectives, ensuring the final solution aligns with your success metrics. You will receive clean, well-documented Python code, performance reports, and visual insights that make results easy to interpret and present.
Whether you need regression or classification, I deliver solutions that are scalable, reproducible, and ready for deployment using industry-standard tools like Python, scikit-learn, MLflow, and FastAPI (if required).
All work is 100% original, professionally structured, and designed to deliver measurable impact — not experiments.
I specialize in building end-to-end ML pipelines covering data preprocessing, feature engineering, model selection, hyperparameter tuning, and performance evaluation. Every project is approached with a strong focus on accuracy, reliability, and real-world usability.
Unlike generic models, I take time to understand your data and objectives, ensuring the final solution aligns with your success metrics. You will receive clean, well-documented Python code, performance reports, and visual insights that make results easy to interpret and present.
Whether you need regression or classification, I deliver solutions that are scalable, reproducible, and ready for deployment using industry-standard tools like Python, scikit-learn, MLflow, and FastAPI (if required).
All work is 100% original, professionally structured, and designed to deliver measurable impact — not experiments.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
BigDL, Keras, MATLAB, MLflow, PyTorch, TensorFlowAI Development Language
PythonWhat's included $220
These options are included with the project scope.
$220
- Delivery Time 7 days
- Number of Revisions 21
- AI Model Integration
- Knowledge Graph
- Model Documentation
Optional add-ons
You can add these on the next page.
Fast 5 Days Delivery
+$5Frequently asked questions
About Pathum
Data Engineer | ETL Pipelines & Telecom Analytics | Python PySpark
Homagama, Sri Lanka - 8:13 pm local time
I build automated ETL pipelines and data systems that eliminate that problem — and I've done it at scale.
At Mobitel (Sri Lanka's national telco), I designed and maintained Python + Airflow pipelines processing 10M+ KPI records per day, reducing manual reporting effort by 40%. I've built anomaly detection systems that cut fault response time by 25%, and SQL-driven dashboards that improved KPI accuracy by 18% across live LTE/VoLTE networks.
What I can build for you:
• Automated ETL pipelines (Python, Airflow, SQL, PySpark)
• Data warehouse design and optimization
• ML pipelines with experiment tracking (MLflow, Scikit-learn)
• Anomaly detection and alerting systems
• Telecom KPI dashboards and analytics (Power BI, Tableau)
I'm currently completing my MSc in Data Science & AI at University of Moratuwa and hold an NVIDIA Accelerated Data Science certification (2026).
My work is production-grade — not tutorial code. Every pipeline I write handles real data at real scale.
Message me with your data problem and I'll tell you in 24 hours whether I can solve it and how.
Steps for completing your project
After purchasing the project, send requirements so Pathum can start the project.
Delivery time starts when Pathum receives requirements from you.
Pathum works on your project following the steps below.
Revisions may occur after the delivery date.
Data Preprocessing & Feature Engineering
Clean missing values, handle outliers, encode features, scale data, and engineer relevant features to maximize model performance.
Model Development & Optimization
Train multiple ML models, tune hyperparameters, and evaluate performance using appropriate metrics. Select the best-performing model.