https://github.com/kanishkrawatt/react-flask

A dashboard that aggregates learning resources from different platforms and presents them to the user based on their preferences, learning style, and areas of interest.
https://github.com/kanishkrawatt/react-flask

Last synced: 11 days ago
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A dashboard that aggregates learning resources from different platforms and presents them to the user based on their preferences, learning style, and areas of interest.

• Host: GitHub
• URL: https://github.com/kanishkrawatt/react-flask
• Owner: Kanishkrawatt
• Created: 2023-11-29T13:45:01.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-02-16T07:07:42.000Z (9 months ago)
• Last Synced: 2024-10-11T13:38:26.173Z (about 1 month ago)
• Language: Jupyter Notebook
• Size: 348 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: Readme.md

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README

        
# Customized Learning Resources Dashboard

Build a dashboard that aggregates learning resources from different platforms and presents them to the user based on their preferences, learning style, and areas of interest.

## Getting Started

For this project , I used the following technologies:

- Frontend: React JS

- Backend: Flask (Python)

- Dataset: Kaggle

- ML monel: Cosine Similarity (NLP)

### Why Cosine Similarity?

Cosine similarity is a metric used to measure how similar the documents are irrespective of their size. Mathematically, it measures the cosine of the angle between two vectors projected in a multi-dimensional space. In this case, the two vectors I am referring to are arrays containing the word counts of two documents.

### Installation

- Clone the repo

```sh

git clone

```

- Install NPM packages

```sh

npm install

```

- Install Python packages

```sh

pip install -r requirements.txt

```

- Run the app

```sh

npm start

```

- Run the backend server

```sh

cd server

# create a virtual environment

python3 -m venv .venv # Linux

py -3 -m venv .venv # Windows

# first activate the virtual environment

. .venv/bin/active # Linux

.venv\Scripts\activate  # Windows

# run the server

flask --app server.py run

or 

python -m flask --app server.py run

```