PANI

Premchand Sepeni

@prem_chand15ai / mlgithub.com/Premchand154

Public-work score

13/50

Cross-checks resume claims against public GitHub work. Higher scores mean stronger corroborating evidence.

Technical Depth
3/10
Experience Authenticity
1/10
Public Contribution
1/10
Claim Consistency
1/10
Domain Fit
7/10

Demonstrated capabilities

RAG Pipelines70% confidence

Project 'AI Codebase Intelligence System' claims 'Developed an AST-based RAG pipeline using SentenceTransformers and FAISS'. Python/Jupyter Notebooks support prototyping RAG systems.

Computer Vision70% confidence

Projects 'Multimodal AI Copilot' and 'AI Vision Copilot' claim usage of YOLOv8, BLIP, and OpenCV. Python/Jupyter Notebooks are core to computer vision development and experimentation.

Classical ML60% confidence

Skills section lists 'Regression, Classification, Support Vector Machines (SVM)' and 'Scikit-learn'. Python and Jupyter Notebooks are commonly used for classical machine learning tasks.

Model Training60% confidence

Internship at Edunet Foundation claims 'Designed and fine-tuned machine learning models'. Python and Jupyter Notebooks are suitable for model training and fine-tuning experiments.

Batch Etl50% confidence

Internship at UptoSkills claims 'Engineered data preprocessing pipelines for large-scale code datasets' and Edunet Foundation internship claims 'Performed data preprocessing, validation, and transformation'. Python is a common tool for batch data processing.

GitHub activity

Verified stack

Jupyter NotebookPythonHTMLCSSDockerfileJavaScript

Key evidence

  • GitHub primary tech stack is 96.2% Jupyter Notebook and 2.9% Python.
  • Total GitHub contributions are 209 (195 commits) over 1.6 years.
  • Zero Dockerfile usage despite claims of using Docker.
  • Zero external open source PRs merged.
  • Only 1 total star across 17 public non-fork repositories.

Scored 29 Jul 2026