Paresh Kumar Palai

Machine Learning Engineer
Bhubaneswar, IN.

About

Highly motivated Machine Learning Engineer with 1+ years of experience specializing in building and deploying scalable ML and data science solutions. Proven ability to leverage Python, TensorFlow, Keras, and MLOps tools (MLflow, Docker, GCP) to deliver high-accuracy models, including a CNN image classifier achieving 93% accuracy and a routing algorithm validated on 10M+ data points. Adept at developing end-to-end pipelines, from data analysis and feature engineering to real-time API deployment, driving significant improvements in efficiency and predictive capabilities.

Work

Accenture
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Technology Apprenticeship (Virtual Program)

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Summary

Completed a virtual technology apprenticeship, focusing on the foundational stages of data solution development and strategic business alignment.

Highlights

Designed a robust data pipeline, meticulously mapping complex business requirements to precise technical tasks for efficient project execution.

Prepared comprehensive documentation and a deployment checklist, ensuring project readiness and facilitating clear communication of business-impact recommendations.

Deloitte
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Data Analytics Simulation (Virtual Internship)

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Summary

Participated in a virtual internship focusing on data analytics, where I executed comprehensive data processing and visualization tasks to derive actionable business insights.

Highlights

Cleaned, transformed, and analyzed over 500K datasets using Python and SQL to prepare data for strategic decision-making and reporting.

Developed interactive dashboards using Power BI and Excel, effectively visualizing key performance indicators (KPIs) and delivering data-driven recommendations.

Education

Tripura University
Agartala, Tripura, India

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MCA

Computer Applications

Jambeswar Mahavidyalaya
Bhubaneswar, Odisha, India

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B.Sc.

Mathematics

Publications

Q-Learning-based Energy-Efficient Custom Cooperative Routing Protocol (QEECCR)

Published by

Science & Technology Journal, Vol. 13, No. 1

Summary

Published a research paper on an innovative Q-learning-based routing protocol designed to enhance energy efficiency and extend the network lifetime of Underwater Wireless Sensor Networks (UWSN).

Certificates

Data Analytics

Issued By

Google

Machine Learning

Issued By

Udemy

Cloud Computing

Issued By

NPTEL (IIT Kharagpur)

Distributed Systems

Issued By

NPTEL (IIT Kanpur)

Python

Issued By

IIT Bombay

Skills

Programming Languages

Python, SQL.

Machine Learning & Deep Learning

TensorFlow, Keras, Scikit-learn, PyTorch, Machine Learning, Deep Learning, Computer Vision, Reinforcement Learning, Regression, Classification, Time Series, NLP, CNN.

MLOps & Cloud Platforms

MLflow, Docker, GCP, FastAPI, Model Deployment, APIs, Scalable Deployment.

Data Analysis & Visualization

Pandas, NumPy, Matplotlib, Power BI, Excel, Data Analytics, Feature Engineering, Customer Segmentation, RFM Analysis, Pareto Analysis.

Version Control

Git.

Big Data Technologies

Apache Spark.

Network Simulation

NS2, AquaSim.

Projects

End-to-End MLOps Pipeline for Real-Time Image Classification

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Summary

Developed and deployed a comprehensive MLOps pipeline for real-time image classification, leveraging advanced deep learning techniques and cloud infrastructure to automate content tagging.

House Price Prediction API using FastAPI and Machine Learning

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Summary

Developed an end-to-end machine learning pipeline and API for house price prediction, integrating data processing, model development, and real-time deployment.

E-commerce Customer Segmentation using RFM Analysis to Drive Targeted Marketing Strategies

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Summary

Executed RFM analysis on a large e-commerce dataset to segment customers, providing data-driven insights to optimize marketing campaigns and improve customer retention.

Q-Learning-based Energy-Efficient Custom Cooperative Routing Protocol (QEECCR)

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Summary

Designed and validated a Q-learning-based routing algorithm for Underwater Wireless Sensor Networks (UWSN), focused on extending network lifetime and optimizing data transmission.

Paresh Kumar Palai