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House price prediction using linear regression (minimal)

Using the boston housing dataset: https://www.kaggle.com/c/boston-housing/

# 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 jovian --upgrade --quiet
WARNING: You are using pip version 20.1; however, version 20.1.1 is available. You should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.
# Imports
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
# Hyperparameters
batch_size=64
learning_rate=5e-7


# Other constants
DATASET_URL = "https://raw.githubusercontent.com/selva86/datasets/master/BostonHousing.csv"
DATA_FILENAME = "BostonHousing.csv"
TARGET_COLUMN = 'medv'
input_size=13
output_size=1

Dataset & Data loaders