Sharat Gujamagadi

Get expert feedback on your Master’s thesis report, internship report, or major project report—especially for Machine Learning / Computer Vision work. I’ll review your report like an evaluator/interviewer would: checking technical correctness, clarity, structure, experiments, and defensibility, and I’ll help you turn it into a stronger academic + industry-ready document.

What you’ll get

• ✅ Deep review of content & structure (storyline, flow, clarity, completeness)
• ✅ Technical feedback (problem framing, assumptions, methodology, math, correctness)
  • ✅ Experiment + evaluation reviewmetrics choice, baselines, ablations, error analysis, dataset splits, robustness
• ✅ Project defensibility upgrades (how to justify design decisions + tradeoffs)
• ✅ Actionable edits & rewrite suggestions (section-by-section)
  • ✅ Final deliverablesprioritized improvement list
  • “ready-for-submission” checklist
  • interview-style questions you should be prepared to answer

Best for

• Students preparing final submission (Master’s/Thesis/Internship)
• Candidates using their report to strengthen resume + interviews
• Anyone who wants their ML/CV work to look clear, rigorous, and credible

What I can review (examples)

• ML/CV pipelines: segmentation, anomaly detection, detection, classification
• Data & evaluation: imbalance, domain shift, reliability, failure modes
• Generative modeling: GAN/VAE-style experiments and reporting
• System considerations: deployment constraints, monitoring, scalability (if included)

How it works

1. You share your report (PDF/Doc) + context (deadline, target: academic vs job)
2. I review and mark key gaps + improvements
3. We do a 1:1 feedback session to explain changes and align next steps

What to send before the session (recommended)

• Report draft (PDF/Doc)
• 1–2 lines: goal + deadline + target audience (professor/company)
• If possible: key results tables/figures + GitHub (optional)