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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..

Recap: Blob detection지난 포스팅에서는 feature point중 하나인 blob에 대하여 살펴보았다. Blob은 이미지에서 주변과 비교했을때 intensity가 다른 영역을 의미한다. Blob을 감지하는 방법은 우선 2D Gaussian function의 Laplacian을 계산한 후 standard deviation의 제곱을 곱하여 scale-normalize를 하고 이 2d filter를 이미지에 convolve를 하였을때의 local maxima를 찾는다. 이때 scale space에서 local maxima들중 가장 response가 큰 optimal sigma가 정해지며, $\frac{\sigma}{\sqrt{2}}$ 가 blob의 radius 가 된다. 하지만 LoG를 사용하..