Simple Solution to Kaggle Titanic Competition

Simple Solution to Kaggle Titanic Competition

Simple Solution to Kaggle Titanic Competition. Shortly after joining Kaggle I received an invitation to partake of a competition to become acquainted with the principles of data science.

In the summer of 2020, right in the middle of the COV19 pandemic, I invested in a new Chrome Book and embarked upon my journey to become a data scientist. I have a Bachelor of Arts in Computer Studies awarded by the University of Maryland three decades ago. When I received my BA, for which I had been on the Dean’s List on at least one occasion, I moved to the UK and was unable to find work in any technical capacity, being relegated to the ranks of personal assistant, secretary, administrator or coordinator.The advent of computer technology, however, has made many of the support roles that I had previously undertaken redundant because computers and machines are able to do the tasks that humans had previously done. For example, software packages have superseded accountants and bookkeepers, with receptionists quite often being assigned the task of entering invoices and other accounting documents into an accounting package.Sensing the need to upgrade my skills in this changing work environment, I looked on the Kaggle site, a company that happens to be owned by Google. Shortly after joining Kaggle I received an invitation to partake of a competition to become acquainted with the principles of data science. I was very daunted when I went onto the competition page and found the Titanic competition. I was not sure how I could enter such a competition with no training in data science, so it took me a while to pluck up the courage to enter the competition. Finally, after several weeks on completing online courses on data science, the Linux operating system, and the Python programming language, I decided it was time to complete the tutorial on entering the Titanic competition and submit my first dataframe of text, the answer being that all women survived. I then submitted the tutorial program that gave a model of the Random Forest Classifier, giving an accuracy rate of 77.51%.It isn’t enough to make a submission based on someone else’s work, so i continued to study python and data science, frequently going back to the Titanic competition, endeavouring to complete the exercise on my own without the assistance of anyone else. The following program, therefore, is my own work and I would like to share it with anyone who wishes to get on the Kaggle leaderboard.The train and test files necessary to complete this exercise can be found on the Kaggle website, but the link can be found at:- https://www.kaggle.com/c/titanic/dataThe problem statement for the Titanic competition is the first starting point to begin work on this project because it gives the entrant an idea of where he can begin to unravel the complexities of using data science to solve the conundrum of who survived the sinking of the Titanic and who perished:-Problem StatementThe sinking of the Titanic is one of the most infamous shipwrecks in history.On April 15, 1912, during her maiden voyage, the widely considered “unsinkable” RMS Titanic sank after colliding with an iceberg. Unfortunately, there weren’t enough lifeboats for everyone onboard, resulting in the death of 1502 out of 2224 passengers and crew.While there was some element of luck involved in surviving, it seems some groups of people were more likely to survive than others.In this challenge, we ask you to build a predictive model that answers the question: “what sorts of people were more likely to survive?” using passenger data (ie name, age, gender, socio-economic class, etc).Strategy to solving this mystery:-

  1. Process data and clean itgraphically represent dataBreak test set up for training purposesselect modelTrain and predict on modelsubmit prediction

I intend on taking the novice step by step to complete the Titanic competition and get on the leaderboard:-

artificial-intelligence python machine-learning data-science titanic

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Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.

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Data Science Projects | Data Science | Machine Learning | Python

Practice your skills in Data Science with Python, by learning and then trying all these hands-on, interactive projects, that I have posted for you.

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