https://github.com/rshrc/sales-forecast-ml

Web app to predict sales of a new product :chart_with_upwards_trend:
https://github.com/rshrc/sales-forecast-ml

clustering css django html linear-regression logistic-regression machine-learning material-design prediction python3 single-page-app sklearn

Last synced: 3 months ago
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Web app to predict sales of a new product :chart_with_upwards_trend:

• Host: GitHub
• URL: https://github.com/rshrc/sales-forecast-ml
• Owner: rshrc
• Created: 2018-08-18T17:35:54.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2024-02-07T19:17:34.000Z (12 months ago)
• Last Synced: 2024-10-12T06:49:10.553Z (3 months ago)
• Topics: clustering, css, django, html, linear-regression, logistic-regression, machine-learning, material-design, prediction, python3, single-page-app, sklearn
• Language: Python
• Homepage:
• Size: 4.53 MB
• Stars: 54
• Watchers: 8
• Forks: 14
• Open Issues: 4
• Metadata Files:
  • Readme: README.md

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README

        
# Sales Forecast using Machine Learning

### A web application to predict the sales of a newly launched product

#### Libraries Used : scikit-learn Web Framework User : Django

##### Using the pickle library to load and use pre trained ml models.

### How does it look like when you run it?

#### Main Page

![MainPage](https://i.imgur.com/mjIUd6T.png)

#### Product Detail Input Page

![ProductInput](https://i.imgur.com/OgrFdvj.png)

#### Prediction Output Page

![PredictionPage](https://i.imgur.com/ywBj5KY.png)

### How to run sales_predit_ml on your Linux/Unix System ?

##### Clone the repository and get inside sales_forecast_ml

```

git clone https://github.com/rshrc/sales_forecast_ml && cd sales_predict_ml

```

##### Installing required Python3 libraries

```

sudo pip3 install -r requirements.txt

```

##### Make Migrations

```

python3 manage.py makemigrations predict && python3 manage.py migrate

```

##### Loading the server_predictor.py for later use

```

python3 ml_core/ml_process/server_predictor.py

```

##### Running the Server

```

python3 manage.py runserver

```

You should now be able to access the sales_predict_ml web app in localhost:8000 in your browser

### How to run sales_predit_ml on your Windows System ?

Install Linux or buy a Mac and revisit https://github.com/rshrc/sales_forecast_ml/README.md