pycaret

# import classification module
from pycaret.classification import *

# init setup
clf1 = setup(data, target = 'name-of-target')

# train adaboost model
adaboost = create_model('ada')

# AUC plot

pycaret

# import classification module
from pycaret.classification import *

# init setup
clf1 = setup(data, target = 'name-of-target')

# train a decision tree model
dt = create_model('dt')

# train a bagging classifier on dt

pycaret

# import classification module
from pycaret.classification import *

# init setup
clf1 = setup(data, target = 'name-of-target')

# return best model
best = compare_models()

# return best model based on Recall

pycaret

# Importing dataset
from pycaret.datasets import get_data

credit = get_data('credit')
# Importing module and initializing setup
from pycaret.classification import *
clf1 = setup(data = credit, target = 'default')

# create a model
xgboost = create_model('xgboost')

pycaret

FROM python:3.7

RUN pip install virtualenv
ENV VIRTUAL_ENV=/venv
RUN virtualenv venv -p python3
ENV PATH="VIRTUAL_ENV/bin:$PATH"

WORKDIR /app
ADD . /app

pycaret

# creating a copy of data
data2 = data.copy()
data2.dropna(axis=0, inplace=True)
data2['Converted'] = data2['Converted'].replace({1 : 'Yes', 0 : 'No'})

# plotly visual
import plotly.express as px

fig = px.scatter(x=data2['Total Time Spent on Website'], y=data2['Asymmetrique Activity Score'], 
                 color = data2['Converted'], template = 'plotly_white', 

pycaret

FROM python:3.7

RUN pip install virtualenv
ENV VIRTUAL_ENV=/venv
RUN virtualenv venv -p python3
ENV PATH="VIRTUAL_ENV/bin:$PATH"

WORKDIR /app
ADD . /app

pycaret

import os, ast
import pandas as pd

dataset = os.environ["INPUT_DATASET"]
target = os.environ["INPUT_TARGET"]
usecase = os.environ["INPUT_USECASE"]

dataset_path = "https://raw.githubusercontent.com/" + os.environ["GITHUB_REPOSITORY"] + "/master/" + os.environ["INPUT_DATASET"] + '.csv'
data = pd.read_csv(dataset_path)
data.head()

pycaret

name: PyCaret AutoML Git Action
on: 
  push :
    branches: [ master ]  
jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - name: PyCaret AutoML Git Action
        id: model

pycaret

name: "PyCaret AutoML Git Action"
description: "A simple example of AutoML created using PyCaret 2.0"
author: "Moez Ali"
inputs:
  DATASET:
    description: "Dataset for Training"
    required: true
    default: "juice"
  TARGET:
    description: "Name of Target variable"