Machine Learning model in Flask 

Machine Learning model in Flask 

If you have created a machine learning(ML) model and you want your friends to try it out, the best way to do is to deploy your model in a flask server. Flask comes way too handy for beginners who wants to work in deployment of ML model. Flask is a micro web framework written on python.

If you have created a machine learning(ML) model and you want your friends to try it out, the best way to do is to deploy your model in a flask server. Flask comes way too handy for beginners who wants to work in deployment of ML model. Flask is a micro web framework written on python.

In this article, we will see how to create an ML model to predict Indian Premier League(IPL) first inning score and deploy it in Flask. If you want to view the app, please click here.

Creating Model:

Our first task is to create model. The data set used for training this model is available in kaggle. The data includes every IPL match statistics from 2008–2017. So, lets load the data set:

Since our data is from 2008, it includes teams that are not playing in current IPL. So lets remove those data. I have made a list of present teams in IPL, and created a new data frame which has batting and bowling team present in the created team list.

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