Sample code for coding practice
Project description
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.
To excute the script
python < scriptname.py >
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
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