The Flavourscape Regression page is dedicated to the art of identifying the subtlest nuances in flavour profiles. Using advanced data science techniques, we've created a system to pinpoint the exact ingredients and ratios that make your dish shine or, conversely, crumble.

Our team of expert chefs and data scientists have developed a proprietary algorithm that takes into account over 500 flavour variables, including but not limited to:

• Umami levels (0-10)
• Acidity (0-10)
• Sweetness (0-10)
• Saltiness (0-10)
• Spiciness (0-10)

By using our Flavourscape Regression tool, you'll be able to:

• Identify the exact ingredients that make or break your dish
• Adjust seasoning ratios to achieve the perfect flavour profile
• Discover hidden patterns in your flavour preferences
• Predict the perfect pairing for your next culinary experiment

Flavourscape Regression Algorithm:
		# Import all the things
		import numpy as np
		import pandas as pd
		import matplotlib as plt

		# Define the flavour variables
		flavour_variables = ['Umami', 'Acidity', 'Sweetness', 'Saltiness', 'Spiciness']

		# Define the flavour ratios
		flavour_ratios = {
			'Umami': 0.5,
			'Acidity': 0.2,
			'Sweetness': 0.8,
			'Saltiness': 0.1,
			'Spiciness': 0.4
		}

		# Define the flavour profile
		flavour_profile = np.dot(flavour_ratios, np.array([1, 1, 1, 1, 1]))

		# Print the flavour profile
		print(flavour_profile)