Flood Prediction

Avilash angirekula is also on the team but his account was flagged

It interested us because it related river levels with rainfall data in order to detect floods. Instead of using linear regression, you could use other machine learning algorithms like decision trees, random forests, or neural networks to create more sophisticated models. These algorithms can handle nonlinear relationships between variables and provide better predictions in some cases.

It Imports necessary libraries such as pandas, numpy, matplotlib, and sklearn. Uploads two CSV files (one containing hourly rainfall data and the other containing hourly river level data) using the Google Colab file uploader. Reads the two CSV files into pandas dataframes and prints out some basic information about the data (e.g. the shape and description of each dataframe). Plots the hourly cumulative rainfall data and hourly river level data using matplotlib. Merges the two dataframes into a single dataframe based on the "Date/Time" column. Drops some unnecessary columns from the merged dataframe. Splits the merged dataframe into training and testing sets. Uses linear regression from the sklearn library to fit a linear model to the training data. Predicts the river level based on the rainfall for the testing set. Plots the training and testing sets with the predicted regression line. Overall, this code seems to be exploring the relationship between rainfall and river level and attempting to fit a linear model to this relationship. We learned how to use simple machine learning models in order to predict simple challenges. Data cleaning issues could have been made. The code assumes that the data in the CSV files is clean and ready to be merged. However, there may be missing or erroneous data in the files that could cause problems when merging or analyzing the data. Visualization limitations also could be a problem The code uses basic matplotlib functions to create visualizations of the data. While this may be suitable for simple exploratory data analysis, more complex visualizations may be required for more in-depth analysis.

Built With

• googlecolab
• sklearn