AIML enthusiast
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AffectiveComputingNPTELPrep
April 18, 2026 – Present
Vibe coded previous year interactive question bank
View ProjectJetsonNano_NetworkIDS
March 16, 2026 – Present
Network IDS with an ML model deployed on a Jetson Nano
View ProjectMayura-4B
March 2, 2026 – Present
Project focused on fine tuning Gemma 3 with curated Kannada corpora
View ProjectOpenClaw_Cerebras_config_tutorial
February 18, 2026 – Present
My configuration guide for using Cerebras APIs with OpenClaw
View ProjectGNN-Defense
February 16, 2026 – Present
Auditable defense mechanism for endpoint calls with the help of GNN
View ProjectPhi2_GRPO-QLoRA
January 16, 2026 – Present
Microsoft Phi2 fine tuned with the OpenAssistant dataset using QLoRA and GRPO training techniques
View ProjectSelfdrivingCarGame_ReinforcementLearning_ERAv4
January 5, 2026 – Present
Project built as part of ERAv4 to train a self driving car in a game environment
View ProjectFlight-Data-Analysis
December 10, 2023 – December 11, 2023
A data analysis project for sem 1 Data set:https://www.kaggle.com/datasets/shubhambathwal/flight-price-prediction?select=Clean_Dataset.csv
View ProjectFFB-Software
September 24, 2021 – September 24, 2021
This repo contains the software to use EMC utility light
View ProjectCultural Fit Analysis
The candidate demonstrates a strong initiative through numerous personal projects, indicating a self-starter mentality and a passion for learning and applying new technologies. The diversity of projects, from LLM fine-tuning to network intrusion detection and data analysis, suggests adaptability and a broad interest in technical challenges. This aligns well with a culture that values continuous learning and proactive problem-solving. However, without information on team-based projects or professional experience, assessing collaboration and interpersonal fit is limited.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, problem-solving approaches, or communication style in a team setting.