Python - Machine Learning Titanic Case Study

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Python - Machine Learning
%3D
Titanic Case Study
Look at the suggestions when you are completely unsure of where to start.
This is an established problem where we will attempt to predict whether a person survived or not
during the titanic accident. There are many features that are given in advance, so you are free to use
the techniques learned during the class. Also, use your personal judgement of the features to decide
in advance what you believe is irrelevant to finding the desired result.
Let's discuss for a bit what the features are.
survival - Survival (0 = No; 1 = Yes)
%3D
line
sibsp - Number of Siblings/Spouses Aboard
parch - Number of Parents/Children Aboard
embarked - Port of Embarkation (0 = Cherbourg; 1 = Queenstown; 2 = Southampton)
%3D
fare - Passenger Fare
sex(male/female)
Passengerid,Age,Fare,Sex,sibsp,zero,zero,zero,zero,zero,zero,zero,Parch,zero,zero,zero,zero,
zero,zero,zero,zero,Pclass,zero,zero,Embarked,zero,zero,survived
The final goal is to predict the last column, which is if the passenger was saved or not. Once you
reach the desired result, try to make a cleaner result. There are many things that you can do to make
a cleaner outcome, such as removing columns of zero as a preprocessing step. Use this to test your
python skills.
Suggestions on how to proceed:
Think if this problem can be approached with linear algorithms or no.
Try to guess which weights will be higher by understanding the features.
Attachments link: https://bit.ly/3txFhH6
Transcribed Image Text:Python - Machine Learning %3D Titanic Case Study Look at the suggestions when you are completely unsure of where to start. This is an established problem where we will attempt to predict whether a person survived or not during the titanic accident. There are many features that are given in advance, so you are free to use the techniques learned during the class. Also, use your personal judgement of the features to decide in advance what you believe is irrelevant to finding the desired result. Let's discuss for a bit what the features are. survival - Survival (0 = No; 1 = Yes) %3D line sibsp - Number of Siblings/Spouses Aboard parch - Number of Parents/Children Aboard embarked - Port of Embarkation (0 = Cherbourg; 1 = Queenstown; 2 = Southampton) %3D fare - Passenger Fare sex(male/female) Passengerid,Age,Fare,Sex,sibsp,zero,zero,zero,zero,zero,zero,zero,Parch,zero,zero,zero,zero, zero,zero,zero,zero,Pclass,zero,zero,Embarked,zero,zero,survived The final goal is to predict the last column, which is if the passenger was saved or not. Once you reach the desired result, try to make a cleaner result. There are many things that you can do to make a cleaner outcome, such as removing columns of zero as a preprocessing step. Use this to test your python skills. Suggestions on how to proceed: Think if this problem can be approached with linear algorithms or no. Try to guess which weights will be higher by understanding the features. Attachments link: https://bit.ly/3txFhH6
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