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Gauri Agrawal

Full Stack Developer AI-ML Enthusiast Student

Hi. I'm
Gauri Agrawal

A passionate and skilled web developer and AI-ML specialist with a passion for creating beautiful, responsive, and user-friendly websites and ML models. I've worked on a variety of web and ML projects ranging from e-commerce platforms to ERP portal.

Riachard Ryan

My Skills

  • HTML/CSS

    Proficient in creating responsive and visually appealing web layouts.

    95%

  • JavaScript

    Skilled in building interactive and dynamic web applications.

    85%

  • Bootstrap

    Skilled in utilizing Bootstrap to create consistent and visually appealing designs.

    95%

  • React.js

    Expert in building user interfaces with React.js, including reusable components and implementation of React Router.

    70%

  • Node.js

    Proficient in building scalable server-side applications with Node.js, with experience working with NoSQL and SQL databases like MongoDB and MySQL.

    70%

  • MySQL

    Expert in designing and optimizing MySQL databases.

    90%

  • PHP

    Proficient in server-side scripting with PHP, skilled in developing dynamic web applications and content management systems, and experienced in integrating PHP with databases like MySQL.

    85%

  • Python

    Expert in Python programming language for web development using Flask frameworks and skilled in data analysis, machine learning, and artificial intelligence with Python.

    75%

  • Machine Learning

    Proficient in ML algorithms, data preprocessing, feature engineering, model evaluation, deep learning concepts and neural network architectures, and experienced in implementing ML models with various libraries.

    70%

  • Flask

    Expert in building scalable and maintainable Flask web applications with Flask microframework, and skilled in integrating Flask with databases like SQLite and PostgreSQL.

    65%

My Recent Work.

Shoe Promo

VoiceLift-Help for Innocent

Website with ML Model

The project aims to address challenges faced by under-trial prisoners in India by leveraging technology for enhanced access to justice, rehabilitation, and legal assistance. VoiceLift is a website connecting prisoners with legal resources and facilitating representation. Additionally, a platform links them with pro-bono lawyers, streamlining the bail process, while the rehabilitation program offers educational, vocational, and mental health support. Expected outcomes include improved legal aid access, rehabilitation outcomes, system transparency, and collaboration in legal proceedings.
Wedding Shot

Pneumonia Detection using X-ray images

ML Model

This project involves developing a machine learning model to detect pneumonia using X-ray images. By analyzing a dataset of chest X-ray images, the model aims to accurately classify whether a patient's X-ray indicates the presence or absence of pneumonia. Through machine learning techniques, such as convolutional neural networks (CNNs), the model will be trained to recognize patterns indicative of pneumonia in the images, enabling automated diagnosis.
Fashion Show

Instagram clone

Website

This project is an Instagram clone, replicating the core functionalities of the popular social media platform. It allows users to create accounts, upload photos, follow other users, like and comment on posts, and explore a feed of content.
Fashion Show

Mental Health Quiz

Flask website - ML Model

This project involves the development of a Flask website integrated with a machine learning model for mental health evaluation. Users fill out a questionnaire, and the machine learning model processes their responses to provide an evaluation of their mental health status. The model analyzes the questionnaire data to assess various aspects of mental health. The Flask framework facilitates the creation of a user-friendly interface, allowing individuals to easily access the mental health evaluation tool.
Jumbo Barger

Facial Expression Recognition

ML Model

This project utilizes Convolutional Neural Network (CNN) methodology along with the OpenCV framework, leveraging TensorFlow and Keras libraries. It aims to predict and recognize facial emotions in images, demonstrating proficiency in classifying facial emotion recognition (FER) from static photos. Through preprocessing methods for enhanced accuracy and feature extraction techniques isolating vital facial features such as the jawline, mouth, eyes, nose, and eyebrows, the model achieves a classification accuracy of 96.16% and a validation accuracy of 62.02%. It effectively distinguishes seven distinct emotions based on facial expressions.
Wedding Shot

Indira Gandhi Delhi Technical University for Women (IGDTUW) ERP Portal

Online Billing System

This project is an ERP portal developed for Indira Gandhi Delhi Technical University for Women (IGDTUW). It streamlines administrative processes and communication within the institution, featuring modules for paper setting, paper evaluation, practical exam conduction, and admin functionalities for data visualization.
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