In this blog, we will build an IPL Score Prediction Model using Lasso, Ridge Regression. We will select the best model based on the model's performance metrics and Hyperparameter Tuning. We will also be building an interactive Flask model. First, we will import the necessary Libraries. Now read the dataset(csv file) and display the top 5 records. Dropping unnecessary columns : Our specific use case features like mid, batsman, bowler, striker, and non-striker would not play a significant role so it’s better to drop them. I know that batsmen can play a role in changing scores, but the problem is that there are tonnes of batsmen that have played in IPL so we can’t operate on these many categories, so it’s better to drop them. PreProcessing : Convert the date column to pandas DateTime column. Then we have to remove teams that are not playing today in IPL and we just have to keep consistent teams. Also, we will take data that is after the 5 overs because the initial stages of th...