NEEL RAJESHBHAI PATEL

A highly motivated and dedicated computer science professional looking for a challenging position to utilize my software skills for the growth of the organization.To become a part of an organization where I can utilize my computer science knowledge and skills for the development of both the organization and myself. Talented Software Developer equipped with great coding, debugging and project management abilities. Accomplishes project goals consistently with elegant, scalable code. Works great with team members under Agile and Scrum frameworks.

• Music
• Sports
• Photography
• Travelling

• Android Yatra 1.0, Parul Institute of Engineering and Technology, 08/03/21, 08/05/21, Android Studio, Workshop based on working with Android Studio to create an application.
• Web Development, Parul Institute of Engineering and Technology, 07/01/21, 07/02/21, HTML, CSS, Workshop based on learning basic web development skills.
• Google Cloud Training, Quicklab, 04/01/21, 05/30/21, Google Cloud, Google Cloud Platform, Training based on Gcloud platform from Quicklabs.

• Date of Birth: 04/11/01
• Gender: Male

• Gcloud
• HTML/CSS
• Andriod Development

• Technologies Used: React.js, Web API, HTML, CSS, JavaScript, Node.js
• Project Overview: Developed a responsive web application using React.js to track live COVID-19 cases globally, leveraging real-time data from public APIs.
• Key Features:Displayed live statistics for confirmed cases, recoveries, and deaths using dynamic charts and visualizations.
  Integrated RESTful Web APIs for real-time data fetching and updates.
  Designed an intuitive user interface with modern styling techniques using HTML and CSS.
  Ensured optimal performance and responsiveness across devices.
  
• Impact: Enabled users to access up-to-date COVID-19 case information efficiently, contributing to public awareness during the pandemic.

 Developed a Virtual AI Health Assistance system utilizing Flask for frontend interface. The system utilizes Natural Language Processing (NLP) techniques to extract user symptoms, followed by word vectorization and content mapping for symptom-to-disease classification.

Functionality:

• Predicts diseases based on user symptoms and provides home remedies for non-serious ailments.
• Implements NLP processing for symptom extraction and classification.
• Utilizes Naive Bayes classification for disease prediction.
• Recommends nearby doctors based on user location using pincode mapping.
  

Technologies Used:

• Flask for frontend development.
• Natural Language Processing (NLP) techniques for symptom extraction and classification.
• Naive Bayes classification for disease prediction.
• Integration of pincode-based location services for doctor recommendations.