I am an aspiring Python Developer currently pursuing a Bachelor of Computer Applications (B.C.A). I build clean, maintainable, and scalable Python applications — from automation scripts and data pipelines to GUI apps and ML experiments.

• Full name: Abhishek M G
• Role: Python Developer (aspiring)
• Email: abhishekmgabhishekmg726@gmail.com
• GitHub: github.com/abhi-abhi86
• LinkedIn: Abhishek M G
• Education: Bachelor of Computer Applications (in progress)

I focus on designing and implementing efficient, maintainable software with Python. I enjoy problem solving, building data workflows, creating web apps, GUI tools, and experimenting with machine learning and NLP models. I emphasize readable code, documentation, and using version control for all projects.

• Languages

  • Python — Proficient

• Core Data & Scientific Stack

  • NumPy — Proficient
  • Pandas — Proficient
  • Matplotlib — Familiar

• Machine Learning & Deep Learning

  • scikit-learn — Familiar / Practical use
  • PyTorch (torch) — Familiar (model training, inference)
  • torchvision — Familiar (vision datasets / transforms)
  • transformers — Familiar (Hugging Face models for NLP)

• Natural Language Processing & Retrieval

  • transformers — Working knowledge (tokenizers, model inference)
  • rank-bm25 — Familiar (BM25 retrieval for keyword ranking)
  • fuzzywuzzy & python-Levenshtein — Familiar (string matching, fuzzy matching)
  • wikipedia (python library) — Familiar (fetching article content)

• Computer Vision & Imaging

  • Pillow — Proficient (image loading, processing)
  • torchvision — Familiar (vision models & transforms)

• GUI

  • PyQt6 — Familiar (building desktop GUI applications)

• Web, Scraping & HTTP

  • requests — Proficient
  • beautifulsoup4 — Familiar (HTML parsing & scraping)

• Geospatial & Mapping

  • geopy — Familiar (geocoding)
  • folium — Familiar (interactive maps)

• Utilities & Integrations

  • openai — Familiar (OpenAI API usage)
  • reportlab — Familiar (PDF generation)
  • rank-bm25 — Familiar (document retrieval)
  • Other helpful libs used: wikipedia, fuzzywuzzy, python-Levenshtein

• Databases & Storage

  • MySQL — Proficient
  • SQLite — Proficient

• Testing & Development Practices

  • Unit testing — Familiar (unittest / pytest)
  • Virtual environments — venv / virtualenv
  • Git — Proficient (feature branches, pull requests)

Notes:

• I included the exact libraries you provided (PyQt6, Pillow, torch, torchvision, transformers, numpy, matplotlib, pandas, scikit-learn, requests, wikipedia, beautifulsoup4, geopy, folium, fuzzywuzzy, python-Levenshtein, reportlab, openai, rank-bm25).
• Proficiency labels are conservative; change any label (Advanced / Proficient / Familiar / Learning) to match how you want to present your experience.

(Replace placeholders below with exact repo links for direct links.)

1. Personal Portfolio (Django)

   • Overview: Django site to showcase projects, resume, and contact info.

2. Data Analysis & ML Experiments (Pandas / scikit-learn / PyTorch)

   • Overview: Data cleaning, model training, evaluation scripts and notebooks.

3. GUI & Tools (PyQt6 / Pillow / reportlab)

   • Overview: Desktop utilities for image processing, report generation, and small productivity tools.

Explore all repositories: https://github.com/abhi-abhi86

• Use virtual environments for each project.
• Keep secrets out of repos (.env / environment variables).
• Document setup and usage in each project README.
• Prefer small, testable functions and unit tests for core logic.

General local setup (example):

1. git clone
2. cd repo
3. python -m venv venv
4. source venv/bin/activate (Windows: venv\Scripts\activate)
5. pip install -r requirements.txt
6. follow project-specific README for migrations/run instructions

• Email: abhishekmgabhishekmg726@gmail.com
• GitHub: @abhi-abhi86
• LinkedIn: Abhishek M G (add your profile URL)

Open to internships, collaborations, and open-source contributions.

• Build a strong portfolio of Python web apps, GUI tools, and ML/NLP projects.
• Contribute to open-source projects and collaborate with other developers.
• Continue improving algorithmic and system design skills.