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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
project_name='02-insurance-linear-regression' # will be used by jovian.commit
jovian.commit(project=project_name)
[jovian] Detected Colab notebook... [jovian] Uploading colab notebook to Jovian... [jovian] Capturing environment.. [jovian] Committed successfully! https://jovian.ai/rajibdasbhagat/02-insurance-linear-regression 
'https://jovian.ai/rajibdasbhagat/02-insurance-linear-regression'

Step 1: Download and explore the data

Let us begin by downloading the data. We'll use the download_url function from PyTorch to get the data as a CSV (comma-separated values) file.

DATASET_URL = "https://hub.jovian.ml/wp-content/uploads/2020/05/insurance.csv"
DATA_FILENAME = "insurance.csv"
download_url(DATASET_URL, '.')
Downloading https://hub.jovian.ml/wp-content/uploads/2020/05/insurance.csv to ./insurance.csv 
HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))

To load the dataset into memory, we'll use the read_csv function from the pandas library. The data will be loaded as a Pandas dataframe. See this short tutorial to learn more: https://data36.com/pandas-tutorial-1-basics-reading-data-files-dataframes-data-selection/