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Backpack Prediction ChallengeGoal: Predict the price of backpacks given various attributes. Evaluated by RMSE metric. $$ RMSE=(\frac{1}{N} \sum^N_{i=1} (y_i-\hat{y_i})^2)^\frac{1}{2} $$ Refer to this challenge here: https://www.kaggle.com/competitions/playground-series-s5e2EDAViewing the first 5 rows of dataset, full_data=pd.read_csv("/kaggle/input/playground-series-s5e2/train.csv")full_data.hea..

Spaceship Titanic The goal of the competition is to predict which passengers aboard the Spaceship Titanic were transported to an alternate dimension after the ship collided with a spacetime anomaly near Alpha Centauri. By analyzing records recovered from the spaceship's damaged computer system, assist rescue crews in locating and saving the lost passengers. DatasetOpening up train.csv data file...

Datasetimport numpy as np # linear algebraimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)import osfor dirname, _, filenames in os.walk('/kaggle/input'): for filename in filenames: print(os.path.join(dirname, filename)) Kaggle itself has a directory /kaggle/input and the train and test dataset are included in this folder. Now opening up the train.csv filetrain_dat..