karanjakhar

#loading required libraries
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
from sklearn.svm import SVR

#loading data 
df = pd.read_csv('boston_train.csv')

#looking at first five rows

karanjakhar

#loading required libraries
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC

#loading data for classification 
df = pd.read_csv('https://query.data.world/s/67p5gkjye5vocfiqm2cuxnrkx4ijim')

#looking at first five rows
df.head()

karanjakhar

#importing required libraries
import pandas as pd
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split

#loading data from a csv file to a pandas Dataframe
df = pd.read_csv('https://query.data.world/s/nsyvxagzhkssbiwytst5vpuvxpwgtb')

#looking at first 5 rows of the data
df.head()

karanjakhar

#importing libraries
from sklearn.linear_model import  LinearRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
import pandas as pd

#loading data
data = pd.read_csv('path of your csv file here.csv')

#getting information 

karanjakhar

#Importing required libraries
from sklearn.linear_model import  LinearRegression
from sklearn.datasets import california_housing
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error

#Downloading dataset
data = california_housing.fetch_california_housing()

#Getting target and features