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pip install awesomeness
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pip install awesomeness

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ashrithssreddy/README.md

πŸ‘¨β€πŸ’» Ash Reddy | Coder β†’ Data Scientist

I write code that helps me think better, build faster and solve deeper. My code spans industries, langiages and toolkits β€” built for reuse across industries, academia and everyday life.

🧱 What I Build

These are designed to work on nearly any real-world dataset β€” across industry and academic use cases.

  • ML Toolkit β†’ A curated collection of machine learning workflows with embedded explanations for fast, reusable implementation.
  • Statistics Toolkit β†’ Applied statistics workflows with explanatory depth, covering A/B testing, hypothesis testing, and introductory statistics.
  • DataFrame Explorer β†’ R package to understand dataframes, reducing data coding time by facilitating familiarity before manipulation.

🧠 For Fun & Mental Sharpness

  • tech-tributes β†’ Creative writeups that reframe iconic tech stories through data/code.
  • times-of-twitter β†’ Data-driven experiments with social media and timelines.
  • bitcoin-utils β†’ A playground for analyzing crypto patterns and building lightweight tooling.

πŸ” Digital Security Learnings

  • zero-digital-footprint β†’ A practical guide for protecting your privacy and managing your digital footprint.
  • digital-homestead-guide β†’ Markdown-based guides for privacy-conscious system setup, software choices and local-first workflows.

πŸ›  Preferred Stack

  • Languages β†’ Python, SQL, R
  • Libraries β†’ Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch
  • Visualization β†’ Plotly, Matplotlib, GGplot2, Looker, Tableau, R-Shiny
  • Big Data & Infra β†’ Apache Spark, Hive, Hadoop, Databricks, AWS Redshift
  • Cloud β†’ Google Cloud, AWS, Airflow

Code is how I think. These repos reflect not just what I’ve built β€” but how I approach problems, stay sharp and document ideas that matter.

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  1. statistics-toolkit statistics-toolkit Public

    My personal toolkit for clean, end-to-end workflows in Applied Statistics β€” built for how I approach A/B testing, hypothesis testing and distributions day to day.

    HTML

  2. ml-toolkit ml-toolkit Public

    [Migration Pending] ML Toolkit is my personal collection of machine learning methods and utilities built for fast, reusable implementation. It covers core steps like preprocessing, modeling, tuning…

    Jupyter Notebook

  3. dataframe-explorer dataframe-explorer Public archive

    Simplify data exploration and preparation in R, enabling quicker insights and reducing the time spent on tedious data manipulations.

    R

  4. tech-tributes tech-tributes Public

    TechTributes is a Twitter bot that posts daily AI-generated poems celebrating influential figures in technology.

    Python

  5. times-of-twitter times-of-twitter Public

    This app extracts tweets from my feed, summarizes them, formats them into a newspaper PDF, and emails it to me every morning.

    HTML