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pip install awesomeness
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pip install awesomeness
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ashrithssreddy/README.md

๐Ÿ‘จโ€๐Ÿ’ป Ash Reddy | Coder โ†’ Data Scientist

I write code that helps me think better, build faster and solve deeper. My code spans industries, langiages and toolkits โ€” built for reuse across industries and academic use cases.

๐Ÿงฑ What I Build

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

๐Ÿง  For Fun

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

๐Ÿ” Data Security

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

๐Ÿ›  Preferred Stack

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

Code is how I think. These repos reflect not just what Iโ€™ve built โ€” 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 Applied Statistics workflows from formal training โ€” built for how I approach A/B testing, hypothesis testing and distributions day to day.

    HTML

  2. ml-toolkit ml-toolkit Public

    Personal collection of machine learning methods and utilities built for fast, reusable implementation. It covers core steps like preprocessing, modeling, tuning, and evaluation โ€” with compact code โ€ฆ

    HTML

  3. genai-for-ds genai-for-ds Public

    [Migration Pending] Learning and experimenting with Generative AI applications from a data scientistโ€™s perspective.

    HTML

  4. 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

  5. tech-tributes tech-tributes Public

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

    Python

  6. 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

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