Pranav Prajapati
Generative AI Engineer
Nashik, Maharashtra, India
Summary
🤩
Rockstar🎓
Top SchoolPranav Prajapati is a Core Developer and ML engineer with four years of experience building production-ready AI systems and contributing to high-profile open-source projects like MindsDB and Keras. He focuses on back-end integrations and model engineering—having implemented MonkeyLearn support in MindsDB, converted NER examples to backend-agnostic Keras Core, and added time-series forecasting models to sktime. At sktime he drives roadmaps, scaled support for Polars dataframes, and integrated transformer-based foundation models (MOIRAI) with PEFT/LoRA finetuning hooks for time-series. Comfortable across RAG pipelines, agentic architectures, and real-world performance tuning, he blends research-grade model work with pragmatic engineering to improve accuracy and latency. Based in Nashik, India, he also organizes local ML meetups, signaling a strong commitment to growing the community around applied ML.
4 years of coding experience
1 year of employment as a software developer
Bachelor of Technology - BTech, Computer Science, Bachelor of Technology - BTech, Computer Science at K.K. Wagh Institute of Engineering Education and Research12, Information Technology, 12, Information Technology at Gokhale Education Societys H.P.T.Arts and R.Y.K.Science College, Nashik 422005
Stackoverflow
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Github Skills (26)
apim10
pytorch10
python10
data-science10
pandas10
machine-learning10
time-series10
forecasting10
keras10
deep-learning10
api10
tensorflow10
neural-network10
forecast10
ai9
Programming languages (5)
Github contributions (5)
sktime/sktime
Oct 2022 - Oct 2024
A unified framework for machine learning with time series
Role in this project:
Data Scientist
Data ScientistContributions:26 reviews, 13 PRs, 102 comments in 2 years 1 month
Contributions summary:Pranav primarily contributed to the sktime repository by implementing and enhancing machine learning models, specifically focusing on time series forecasting. They added a new `NeuralForecastLSTM` model, integrating it with the `neuralforecast` library. The user also modified existing documentation and fixed minor bugs related to data loading and registry functions. Furthermore, the user updated the `NeuralForecast` models to support the optimizer parameter, further showcasing their work in model development.
forecastingtime-series-analysistime-series-regressiondata-sciencedeep-learning
mindsdb/mindsdb
Mar 2023 - Feb 2024
AI's query engine - Platform for building AI that can learn and answer questions over large scale federated data.
Role in this project:Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:13 reviews, 17 PRs, 61 comments in 10 months
Contributions summary:Pranav significantly contributed to integrating the MonkeyLearn ML service into the MindsDB platform. They implemented a handler for MonkeyLearn, enabling the platform to utilize its classification capabilities. The contributions include creating initialization files, defining the handler's structure, and implementing the prediction and description methods. Furthermore, they addressed API error handling, refined variable names, and fixed batch prediction errors.
localaimachine-learning-databasesolacesinglestoreexplainable-ml
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