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stocks-project
April 22, 2026 – Present
This repository is based on Stock Prediction using AAPL-stock-data. Here, we have used Qwen1.5-0.5b model and LSTM model to predict the stock and prepared a compact Machine Unlearning module/methods to act whenever poisoned is getting injected into the dataflow. Therefore, it ensures a accurate prediction of yfinance stock with following trends.
View Projectunlearn-plm
April 14, 2026 – Present
This repository teaches you, how you can train a pre-trained language model with large scale data and make it unlearn to prevent model hallucinating. Here, we used a set of methods like gradient ascent, descent with KL divergence to prevent regularization.
View ProjectNeon-Type-Racer
August 11, 2025 – August 15, 2025
Check and improve your typing speed with Neon Type Racer
View ProjectCultural Fit Analysis
The candidate's projects are diverse, covering web development, game development, and machine learning. While this shows a broad interest, the direct alignment with a 'Mobile Application Developer' role is limited to one Dart project ('HungCoders'). The majority of projects are personal and academic in nature, which may indicate a strong self-starter, but also a lack of professional team-based project experience. The breadth of technologies (Python, JavaScript, Dart, Zig, C++) suggests adaptability but also a potential lack of deep specialization in mobile-specific ecosystems.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.