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ML Part of Product Based Bangkit Capstone Project Team C22-PS316

Python 5.01% Jupyter Notebook 94.62% Dockerfile 0.36% Procfile 0.01%

nanamyuk-ml's Introduction

NanamYuk-ML

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ML Part of Product Based Bangkit Capstone Project Team C22-PS316

Machine Learning Team

Name Bangkit ID Contacts
Muhammad Syah Zichrullah Habibie M2322F2811 Github
Naufaldi Hafidhigbal M2224W2072 Github

What we do?

We are making a crop recommendation system for recommending the top 5 crops to be grown based on the users city and environment.

Built with

Flowchart

Flowchart

API Endpoint

Click here ( Deployed using Google Cloud Run )

Endpoint

Endpoint Method Return
/predict GET JSON

Parameters

Parameter Expected input Explanation
city str(city name) -
soil int(1, 2 or 3) 1: Pasir, 2: Lempung, 3: Liat
light int(1 or 2) 1: Full sun, 2: Semi shade

How to run this Flask app locally

  • Clone this repo
  • Open terminal and go to this project's root directory
  • Create your own OpenWeatherMap API_KEY (*Notes)
  • Create a config.py file and type api_key="your_api_key" then save
  • Create and activate a python virtual environment if you want
  • Type pip install -r requirements.txt
  • Serve the Flask app by typing flask run
  • It will run on http://127.0.0.1:5000

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