# flask_api

**Repository Path**: zheng7yan/flask_api

## Basic Information

- **Project Name**: flask_api
- **Description**: Creating a Machine Learning API using Flask - Repository for AV Article
- **Primary Language**: HTML
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-07-31
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

## [Creating Machine Learning API using Flask](https://www.analyticsvidhya.com/blog/2017/09/machine-learning-models-as-apis-using-flask/)
#### Code accompanying the AnalyticsVidhya article

#### How to setup the Anaconda environment:

- Make sure you have __Anaconda distribution__, if not then visit: [Miniconda Installation](https://conda.io/miniconda.html) to install it.
- For a faster installation, run command (on terminal): `curl -L mini.conda.ml | bash` (Courtesy: [@mikb0b](https://twitter.com/mikb0b))
- For any queries regarding conda environment, visit: [Managing Conda Environments](https://conda.io/docs/user-guide/tasks/manage-environments.html)
- Go to the folder `./flask_api`, you'll encounter `flask_api.yml` file.
- In the terminal run command: `conda env create -f flask_api.yml`
- Once done, run: `source activate flask_api`. Your virtual environment is setup successfully!