10000 Daniyal-Qureshi (Daniel) · GitHub
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Achievement: Pull Sharkx3Achievement: YOLOAchievement: Arctic Code Vault Contributor

Achievements

Achievement: Pull Sharkx3Achievement: YOLOAchievement: Arctic Code Vault Contributor

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Daniyal-Qureshi/README.md

Daniyal Qureshi

Daniyal-Qureshi Daniyal-Qureshi total stars


Open Source Contributions

Validator.js - Popular string validation library with 21k+ stars

Contributed to validator.js by implementing new validation methods and fixing bugs



tools Languages | Tools tools

Flutter Android React PostgreSQL mysql mongo firebase AWS heroku gcp Android Studio vs Linux Sass NodeJS Photoshop github git

🔰 Some of my projects



Dicebear Hangman-Game C/C++ QBasic

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  1. EmoWave-Flaskify EmoWave-Flaskify Public

    Trained a Deep Learning MLP classifier to detect emotions based on voice inputs accurately. The classifier was designed to classify emotions into five targeted classes: calm, disgust, fearful, hap…

    Python

  2. nameday_api_gem nameday_api_gem Public

    NamedayApi is a custom Ruby gem that provides a simple interface to fetch nameday information from the "nameday.abalin.net" API. Namedays are a tradition in many countries where each day of the yea…

    Ruby 1

  3. Fitness_App Fitness_App Public

    Fitness App is a workout tracking application that allows users to log exercises, track progress, and analyze workout data. It features a scrollable day selector, enabling users to navigate through…

    Dart 1

  4. URL-Shortner URL-Shortner Public

    This is a URL shortening platform with integrated analytics and user management. It allows users to shorten long URLs, track clicks on the shortened links, and view analytics like unique clicks, ge…

    Python

  5. LLM-Chatbot-in-React LLM-Chatbot-in-React Public

    Developed a Chatbot to parse PDFs, segment text into sentences, tokenize them, generate embeddings, and store them in Supabase. Applied a 0.7 threshold for contextual accuracy, ensuring precise res…

    TypeScript 2

  6. WA-GPT WA-GPT Public

    WhatsApp-based Retrieval-Augmented Generation (RAG) system allows users to upload documents, extract text, generate FAQs, and interact with the content using natural language queries. The system le…

    TypeScript 1

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