housing-library-5496 0.1

Sample code for coding practice

mle-training

Median housing value prediction

The housing data can be downloaded from https://raw.githubusercontent.com/ageron/handson-ml/master/. The script has codes to download the data. We have modelled the median house value on given housing data.

The following techniques have been used:

• Linear regression
• Decision Tree
• Random Forest

Steps performed

• We prepare and clean the data. We check and impute for missing values.
• Features are generated and the variables are checked for correlation.
• Multiple sampling techinuqies are evaluated. The data set is split into train and test.
• All the above said modelling techniques are tried and evaluated. The final metric used to evaluate is mean squared error.

Command to create Virtual Enviornemnt:

conda --version conda create --name mle-dev biopython conda activate mle-dev

install the necessary librabries like numpy,pandas , matplotlib and scikit learn

conda install numpy conda install pandas conda install matplotlib

To excute the script

python < scriptname.py > python nonstandardcode.py

Exporting the enviorment

conda export --name MLE-training >env.yml