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Features Full Stack Development: Utilized NestJS to create a robust and scalable backend for web applications . JWT Authentication: Implemented secure authentication using JSON Web Tokens (JWT) with NestJS and Mongoose. AI and ML Integration: Integrated AI and ML models into the application to enhance functionality and provide innovative features.

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nithieshnaik/Task-Management-Backend

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A progressive Node.js framework for building efficient and scalable server-side applications.

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Description

Nest framework TypeScript starter repository.

Installation

$ npm install

Running the app

# development
$ npm run start

# watch mode
$ npm run start:dev

# production mode
$ npm run start:prod

Test

# unit tests
$ npm run test

# e2e tests
$ npm run test:e2e

# test coverage
$ npm run test:cov

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License

Nest is MIT licensed.

Task-Management-Backend

This repository contains the backend code for my software development internship project focused on full stack development using NestJS. During this internship, I worked on integrating AI and ML models into the backend application to enhance functionality and provide innovative features.

Features Full Stack Development: Utilized NestJS to create a robust and scalable backend for web applications. JWT Authentication: Implemented secure authentication using JSON Web Tokens (JWT) with NestJS and Mongoose. AI and ML Integration: Integrated AI and ML models into the application to enhance functionality and provide innovative features. Real-life Production Projects: Collaborated with senior team members and the CTO to work on real-life production-level projects, gaining hands-on experience in the software development lifecycle. Technologies Used Backend: NestJS, Node.js, Mongoose Authentication: Passport.js, JWT Database: MongoDB Other: Docker, Git, GitHub

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Features Full Stack Development: Utilized NestJS to create a robust and scalable backend for web applications . JWT Authentication: Implemented secure authentication using JSON Web Tokens (JWT) with NestJS and Mongoose. AI and ML Integration: Integrated AI and ML models into the application to enhance functionality and provide innovative features.

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