Amanjeet Sahu
Bengaluru, Karnataka, India
Summary
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SeniorAmanjeet Sahu is a Machine Learning Engineer based in Bengaluru with 8 years of experience building production ML systems, particularly in forecasting, classification, and anomaly detection for utility-scale water networks. At SmartTerra he productionized models with Kubeflow, implemented DVC and Great Expectations for MLOps, and delivered practical gains like improved leak localization and a 75% recall classifier that boosted revenue. He is deeply curious about NLP and deep learning—his GitHub showcases coursework and hands-on implementations in sentiment analysis, Naive Bayes, and logistic regression from the deeplearning.ai NLP specialization. Comfortable across Python, Scala, R and C++, Aman combines data storytelling and engineering skills to turn messy time series and geospatial signals into actionable KPIs and APIs. Colleagues describe him as scrappy and persistent: he emphasizes grit, continuous learning, and pragmatic solutions that move models from experiments to impact.
8 years of coding experience
Github Skills (6)
logistic-regression10
machine-learning10
python10
natural-language-processing10
numpy10
nlp9
Programming languages (3)
Github contributions (5)
amanjeetsahu/Natural-Language-Processing-Specialization
Jul 2020 - Sep 2020
This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera
Role in this project:
ML Engineer
ML EngineerContributions:20 commits, 18 pushes, 1 branch in 2 months
Contributions summary:Amanjeet's commits primarily focus on implementing and modifying code within an iPython notebook related to a Natural Language Processing specialization. The code includes feature extraction, logistic regression, and sentiment analysis on tweets. Furthermore, the commits contain code for Naive Bayes and the implementation of the Sigmoid Function.
natural-language-processingnatural-language-understandingnatural-language-generationnlpnlp-machine-learning
amanjeetsahu/Apache-Spark-Tutorials
Jun 2020 - Dec 2021
This repo contains my learnings and practice notebooks on Spark using PySpark (Python Language API on Spark). All the notebooks in the repo can be used as template code for most of the ML algorithms and can be built upon it for more complex problems.
Contributions:12 commits, 1 PR, 10 pushes in 1 year 5 months
machine-learningpysparkpythonsparkbig-data
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