how to connect an ml model to a web application
#import libraries
import numpy as np
from flask import Flask, render_template,request
import pickle#Initialize the flask App
app = Flask(__name__)
model = pickle.load(open('model.pkl', 'rb'))how to connect an ml model to a web application
#import libraries
import numpy as np
from flask import Flask, render_template,request
import pickle#Initialize the flask App
app = Flask(__name__)
model = pickle.load(open('model.pkl', 'rb'))how to connect an ml model to a web application
#default page of our web-app
@app.route('/')
def home():
return render_template('index.html')how to connect an ml model to a web application
# How To add ML to web. Go from down to up. Pleasehow to connect an ml model to a web application
import pandas as pd
from sklearn.linear_model import LinearRegression
import pickle
df = pd.read_csv("FuelConsumption.csv")
#use required features
cdf = df[['ENGINESIZE','CYLINDERS','FUELCONSUMPTION_COMB','CO2EMISSIONS']]
#Training Data and Predictor Variable
# Use all data for training (tarin-test-split not used)
x = cdf.iloc[:, :3]
y = cdf.iloc[:, -1]
regressor = LinearRegression()
#Fitting model with trainig data
regressor.fit(x, y)
# Saving model to current directory
# Pickle serializes objects so they can be saved to a file, and loaded in a program again later on.
pickle.dump(regressor, open('model.pkl','wb'))
'''
#Loading model to compare the results
model = pickle.load(open('model.pkl','rb'))
print(model.predict([[2.6, 8, 10.1]]))
'''how to connect an ml model to a web application
#To use the predict button in our web-app
@app.route('/predict',methods=['POST'])
def predict():
#For rendering results on HTML GUI
int_features = [float(x) for x in request.form.values()]
final_features = [np.array(int_features)]
prediction = model.predict(final_features)
output = round(prediction[0], 2)
return render_template('index.html', prediction_text='CO2 Emission of the vehicle is :{}'.format(output))how to connect an ml model to a web application
if __name__ == "__main__":
app.run(debug=True)Copyright © 2021 Codeinu
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