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https://github.com/mathealgou/ml-jobs
This project is a machine learning exercise, the application receives a set of skills from the user and returns a job title that matches the skills entered. It uses the Random Forest algorithm to make the prediction base on a jobs dataset.
https://github.com/mathealgou/ml-jobs
machine-learning python random-forest-classifier scikit-learn
Last synced: 17 days ago
JSON representation
This project is a machine learning exercise, the application receives a set of skills from the user and returns a job title that matches the skills entered. It uses the Random Forest algorithm to make the prediction base on a jobs dataset.
- Host: GitHub
- URL: https://github.com/mathealgou/ml-jobs
- Owner: mathealgou
- Created: 2023-12-23T21:36:12.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-12-23T22:27:44.000Z (about 1 year ago)
- Last Synced: 2024-04-24T09:40:19.890Z (9 months ago)
- Topics: machine-learning, python, random-forest-classifier, scikit-learn
- Language: Python
- Homepage:
- Size: 891 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
Awesome Lists containing this project
README
# Job Searcher (Machine Learning exercise 🤖)
## 📖 Description
This project is a machine learning exercise, the application receives a set of skills from the user and returns a job title that matches the skills entered. It uses the [Random Forest algorithm](https://en.wikipedia.org/wiki/Random_forest) to make the prediction base on a [jobs dataset](https://www.kaggle.com/datasets/bishop36/jobs-data). You can also watch the [demo video](https://www.youtube.com/watch?v=TaRlhW6fiT4&ab_channel=MatheusGoulart).
- [Job Searcher (Machine Learning exercise 🤖)](#job-searcher-machine-learning-exercise-)
- [📖 Description](#-description)
- [⚙️ Installation](#️-installation)
- [Requirements:](#requirements)
- [Steps:](#steps)
- [▶️ Usage](#️-usage)
## ⚙️ Installation
### Requirements:
You need to have [Python](https://www.python.org/downloads/) and [venv](https://docs.python.org/3/library/venv.html) installed in your computer.
### Steps:
1. Download and extract the project.
2. Open a terminal and navigate to the project's directory. (Alternatively, navigate to the project's directory and open a terminal).
3. Create a virtual environment with the following command:
```bash
python -m venv .venv
```
4. Activate the virtual environment with the following command:
Windows:
```bash
.venv\Scripts\activate
```
Linux:
```bash
source .venv/bin/activate
```
5. Install the project's dependencies with the following command:
```bash
pip install -r requirements.txt
```
6. Run the application with the following command:
```bash
python main.py
```
Note that, if your terminal application is not set to do this automatically, you will need to activate the virtual environment every time run the application on a new terminal.
## ▶️ Usage
1. (Optional) Activate the virtual environment with the following command:
Windows:
```bash
.venv\Scripts\activate
```
Linux:
```bash
source .venv/bin/activate
```
2. Run the application with the following command:
```bash
python main.py
```