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Showing posts from February, 2021

Titanic - Machine Learning from Disaster

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This is my first Kaggle work where I have published my prediction and have improved my accuracy for the  Titanic - Machine Learning from Disaster. I had followed many notebooks and tutorials for creating this notebook . The Work      After a lot of studying and references to a lot of notebooks, I finally was able to understand this notebook . It is using a  LogisticRegression model to obtain the prediction.     The interesting things that I gathered from this notebook are that it had custom functions to get all the missing data and also many graphs to illustrate the missing data in both the training and the test datasets.     Also, it is using a method to  factorize the data for normalization and filling out the NaN's as -999 for Age and Fare. There was a detailed report taken with the use of the pandas_profiling library.     With this as a base, I started my analysis.     To improve the score from 0.77511 all I had ...