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Data Scientist and Researcher

Nirmal Parmar

Dr. Nirmal Parmar, Ph.D.

  • 🔭 I’m currently working on the integration of Mathematical Gnostics (MG) with Machine Learning (ML)
  • 🌱 I’m currently learning and exploring possible ways/methods/applications to develop ML solutions based on a non-statistical method
  • 👯 I’m open to collaborate on data analysis, thermal engineering, and machine learning projects.
  • 📫 How to reach me: LinkedIn, Google Scholar, ResearchGate, Medium
  • ⚡ Fun fact: 'You are Awesome!'

Selected Projects - Public Access

Theme Projects
Renewable Energy swhML
MG with Machine Learning microDSC, MGMA
Critical Data Analysis LegendreRegression
Thermal Engineering PulseHeatPipe, SPEM, TCR

Python Library - Public Access

Library Description
PyPulseHeatPipe PyPulseHeatPipe is a Python Library for data analysis and for data plotting/visualization specifically for PHP experimental data.
PyCpep PyCpep library predicts the deviation in the isobaric heat capacity measurement (at 298~K) due to the improper amount of the sample or/and calibration standard in Tian-Calvet microDSC.
PyCpep library works on the well-trained artificial neural network (ANN) model coupled with mathematical gnostic.
PyCpil PyCpil is a library to calculate isobaric heat capacity of ionic liquids and ionanofluids (nanofluids).
PyThermalAnalysis PyThermalAnalysis is a python library to perform energy-exergy analysis

Tool Box

PythonMacOS bash Anaconda Fedora GitHub Jupyter Kaggle Latex Linux Matlab MongoDB NumPy Pandas ssh svn TensorFlow Vim VScode Scikit-learn Casandra Matplotlib Octave PySpark seaborn tableau Deltalake databricks MLflow

Nirmal Parmar's Projects

magcalml icon magcalml

COMING SOON: A machine and deep learning library based on the 'magcal' platform. The 'magcal' aka 'mathematical gnostics calculations' platform is based on non statistical theories and methods.

microdsc_error_prediction icon microdsc_error_prediction

ML model to predict an error in the isobaric heat capacity measurement by microDSC that may arise due to an inappropriate amount of the sample or/and calibration standard material

microdsc_error_prediction_ann icon microdsc_error_prediction_ann

Prediction in heat capacity measurement deviation due to improper amount of the sample or/and calibration standard in Tian-Calvet microDSC

pulseheatpipe icon pulseheatpipe

Pulsating Heat Pipe (PHP): Advanced data analysis and Machine Learning

pycpep icon pycpep

pip package to predict the deviation in the heat capacity measurement for microDSC Tian-Calvet

pycpil icon pycpil

PyCpil is a pkg to calculate isobaric heat capacity of ionic liquids and ionanofluids (nanofluids).

pypulseheatpipe icon pypulseheatpipe

The data analysis Python package for the Pulsating Heat Pipe experimental data

scrubber icon scrubber

A python library to clean data and to perform feature engineering easely

spem_prediction icon spem_prediction

Salt Production Enhancement Method (SPEM): Deep Learning (ANN) data driven solution to predict the salt production

tcr_deeplearning icon tcr_deeplearning

Artificial Neural Network (ANN) to predict the Thermal Contact Resistance (TCR)

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