Red Wine Quality Prediction

The two datasets are related to red and white variants of the Portuguese "Vinho Verde" wine. The dataset has the results of physicochemical (inputs) and sensory (the output) variables.

Input variables (based on physicochemical tests):

1 - fixed acidity

2 - volatile acidity

3 - citric acid

4 - residual sugar

5 - chlorides

6 - free sulfur dioxide

7 - total sulfur dioxide

8 - density

9 - pH

10 - sulphates

11 - alcohol

Output variable (based on sensory data):

12 - quality (score between 0 and 10)

!pip install jovian --upgrade --quiet

project_name='linear-regression'

import torch
import jovian
import torchvision
import torch.nn as nn
import pandas as pd
import matplotlib.pyplot as plt
import torch.nn.functional as F
from torchvision.datasets.utils import download_url
from torch.utils.data import DataLoader, TensorDataset, random_split
import matplotlib
import seaborn as sns

dataframe= pd.read_csv("../input/red-wine-quality-cortez-et-al-2009/winequality-red.csv" , delimiter=',')