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Age of death prediction using linear regression

Using the WHO life expectancy dataset: https://www.kaggle.com/kumarajarshi/life-expectancy-who/data#

# Uncomment and run the commands below if imports fail
!conda install numpy pytorch torchvision cpuonly -c pytorch -y
!pip install matplotlib --upgrade --quiet
!pip install pandas
!pip install seaborn
!pip install jovian --upgrade --quiet
Collecting package metadata (current_repodata.json): done Solving environment: failed with initial frozen solve. Retrying with flexible solve. Solving environment: done ==> WARNING: A newer version of conda exists. <== current version: 4.9.0 latest version: 4.9.2 Please update conda by running $ conda update -n base conda Collecting package metadata (repodata.json): \ Requirement already satisfied: pandas in /opt/conda/lib/python3.8/site-packages (1.1.3) Requirement already satisfied: python-dateutil>=2.7.3 in /opt/conda/lib/python3.8/site-packages (from pandas) (2.8.1) Requirement already satisfied: pytz>=2017.2 in /opt/conda/lib/python3.8/site-packages (from pandas) (2020.1) Requirement already satisfied: numpy>=1.15.4 in /opt/conda/lib/python3.8/site-packages (from pandas) (1.19.2) Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas) (1.15.0) Requirement already satisfied: seaborn in /opt/conda/lib/python3.8/site-packages (0.11.0) Requirement already satisfied: scipy>=1.0 in /opt/conda/lib/python3.8/site-packages (from seaborn) (1.5.2) Requirement already satisfied: matplotlib>=2.2 in /opt/conda/lib/python3.8/site-packages (from seaborn) (3.3.3) Requirement already satisfied: pandas>=0.23 in /opt/conda/lib/python3.8/site-packages (from seaborn) (1.1.3) Requirement already satisfied: numpy>=1.15 in /opt/conda/lib/python3.8/site-packages (from seaborn) (1.19.2) Requirement already satisfied: python-dateutil>=2.1 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (2.8.1) Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (0.10.0) Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (8.0.0) Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (1.2.0) Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=2.2->seaborn) (2.4.7) Requirement already satisfied: pytz>=2017.2 in /opt/conda/lib/python3.8/site-packages (from pandas>=0.23->seaborn) (2020.1) Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.8/site-packages (from python-dateutil>=2.1->matplotlib>=2.2->seaborn) (1.15.0)
# Imports
import torch
import jovian
import torchvision
import torch.nn as nn
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import torch.nn.functional as F
from torchvision.datasets.utils import download_url
from torch.utils.data import DataLoader, TensorDataset, random_split
# Other constants
DATASET_URL = "https://raw.githubusercontent.com/Federico-abss/pytorch_gans/master/datasets/life_expectancy_data.csv"
DATA_FILENAME = "life_expectancy_data.csv"
input_size=6
output_size=1
# Download the data
download_url(DATASET_URL, '.')
dataframe = pd.read_csv(DATA_FILENAME)

dataframe.describe()
HBox(children=(HTML(value=''), FloatProgress(value=1.0, bar_style='info', layout=Layout(width='20px'), max=1.0…