How to create predictive models in Python using Jupyter

How to create predictive models in Python using Jupyter

A simple guide to creating Predictive Models in Python, In this python tutorial we will talk about What is predictive model in python? Predictive modeling is a process that uses data mining and probability to forecast outcomes. Each model is made up of a number of predictors, which are variables that are likely to influence future results. In this python predictive analytics tutorial, we will talk about how to predictive anlaytics using Jupyter notebook and i have also taught, how you can predict the price of a house ,using the boston housing data set. This data set has prices of house along with the factors that has an impact on the house price. We looked at the relationship between price and many other variables and then looked at the distribution of data using histogram. Also we took a look at log transformation to understand the distribution of data which is usually not apparent with the actual data values. We also looked briefly on how you can treat missing values in a data set.

We have used library like pandas, matplotlib, numpy, sklearn, statsmodels, seaborn etc. to help understand the data exploration, cleaning and visualization. Finally we created statistical models with the help of the statsmodels and sklearn libraries.

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