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: [email protected]
- 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.
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Languages
- Python — Proficient
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Core Data & Scientific Stack
- NumPy — Proficient
- Pandas — Proficient
- Matplotlib — Familiar
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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)
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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)
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Computer Vision & Imaging
- Pillow — Proficient (image loading, processing)
- torchvision — Familiar (vision models & transforms)
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GUI
- PyQt6 — Familiar (building desktop GUI applications)
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Web, Scraping & HTTP
- requests — Proficient
- beautifulsoup4 — Familiar (HTML parsing & scraping)
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Geospatial & Mapping
- geopy — Familiar (geocoding)
- folium — Familiar (interactive maps)
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Utilities & Integrations
- openai — Familiar (OpenAI API usage)
- reportlab — Familiar (PDF generation)
- rank-bm25 — Familiar (document retrieval)
- Other helpful libs used: wikipedia, fuzzywuzzy, python-Levenshtein
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Databases & Storage
- MySQL — Proficient
- SQLite — Proficient
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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.)
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Personal Portfolio (Django)
- Overview: Django site to showcase projects, resume, and contact info.
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Data Analysis & ML Experiments (Pandas / scikit-learn / PyTorch)
- Overview: Data cleaning, model training, evaluation scripts and notebooks.
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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):
- git clone
- cd repo
- python -m venv venv
- source venv/bin/activate (Windows: venv\Scripts\activate)
- pip install -r requirements.txt
- follow project-specific README for migrations/run instructions
- Email: [email protected]
- 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.




