sharpcodex / nsos Goto Github PK

1. Summary
2. Dependencies
3. Files Structure
4. Instructions
5. ScreenShots

this repository contains helpers files to :

• load Figure Eight disaster data.
• train, and save a machine learning model.
• classify disaster messages

You will need to add the following packages to the default anaconda packages

• sqlalchemy : conda install -c anaconda sqlalchemy
• nltk : conda install -c anaconda nltk
• flask : conda install -c anaconda flask

• data
  • process_data.py: A command line script to read, clean, and save data into a sqlLite database file.
• models
  • train_classifier.py: A command line script to create, train, and save a machine learning model to classify the provided data.
• app
  • run.py: An http server to serve the statistics and classifying web pages.
  • templates/go.html : classification page html file.
  • templates/master.html : statistics page html file.

1. Run the following commands in the project's root directory to set up your database and model.

   • To run ETL pipeline that cleans data and stores in database python data/process_data.py data/disaster_messages.csv data/disaster_categories.csv data/DisasterResponse.db
   • To run ML pipeline that trains classifier and saves python models/train_classifier.py data/DisasterResponse.db models/classifier.pkl

2. Run the following command in the app's directory to run your web app. python run.py

3. Go to http://127.0.0.1:3001/