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šŸ’« About Me:

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Few resources are as follows:

Let's connect on linkedin: : LinkedIn


šŸ”­ Iā€™m a data enthusiast with a background in astrophysics.

šŸŒ± Iā€™m passionate about data analytics, data engineering, machine learning, and deep learning.

šŸ’¬ Ask me about data analysis, machine learning, and ETL pipelines.

šŸ“« You can reach me at [email protected].

šŸŒ Socials: I am also available on: LinkedIn Twitter Facebook Instagram

āš” Fun fact: crazy about football.

šŸ“ Address: Observable Universe/Virgo Supercluster/Milky Way Galaxy/Solar System/Earth/Europe/Germany

Feel free to explore my repositories and projects, and don't hesitate to reach out for collaboration or discussions!

šŸ“š Blog post

Medium Discord Patreon

šŸ’» Tech Stack:

  • Programming Languages:

    • Python Pandas NumPy Matplotlib Seaborn Plotly SciPy

    • Machine Learning Deep Learning scikit-learn Statsmodels TensorFlow PyTorch

    • Mathematica

  • Visualization:

  • DATABase & tools: SQL MySQL NoSQL MongoDB Google BigQuery Postgres

  • Big Data: PySpark Scala Spark Kafka Neo4j Hadoop Apache Spark

  • Technology Stack: AWS Google Cloud Platform (GCP) EC2 S3 Lambda Snowflake Snowpipe Apache Airflow

  • Web Development: HTML5 CSS3 Beautiful Soup Selenium Dash FastAPI Flask

  • Bash and shell Scripting: Shell Scripting APIs CI/CD Pipelines Unit Test

  • Documentation: LaTeX

  • Software and tools: Anaconda

šŸ“Š GitHub Stats:



šŸ” Top Contributed Repo

šŸ† GitHub Trophies


šŸ’° My Open Source Contributions

Patreon BuyMeACoffee

Founding member of Vision Analytica.

Dr. Arun Kumar Pandey's Projects

arunp77 icon arunp77

Config files for my GitHub profile.

bharatcart icon bharatcart

A portal for the system design of the e-commerce business

eda-series-terrorism icon eda-series-terrorism

Exploratory Data Analysis, or EDA, is essentially a type of storytelling for statisticians. It allows us to uncover patterns and insights, often with visual methods, within data. EDA is often the first step of the data modelling process

llm-course icon llm-course

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

parameter_estimation_by_minimising_chi_square icon parameter_estimation_by_minimising_chi_square

This code cover most basic way to estimate best fit parameters for a given dataset and model by chi-square minimisation. This analysis based on Hubble dataset with Flat LCDM model with two parameters.

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