Beginner Data Science Portfolio Project Walkthrough (Kaggle Titanic)

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Welcome to my data science journey through the Kaggle Titanic - Machine Learning from Disaster Project!

In this video, we'll dive deep into the world of data analysis, feature engineering, and machine learning to predict passenger survival rates on the Titanic.

As Kaggle states: "The competition is simple: use machine learning to create a model that predicts which passengers survived the Titanic shipwreck."

Interested in discussing a Data or AI project? Feel free to reach out via email or simply complete the contact form on my website.

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WHO AM I?
As a full-time data analyst/scientist at a fintech company specializing in combating fraud within underwriting and risk, I've transitioned from my background in Electrical Engineering to pursue my true passion: data. In this dynamic field, I've discovered a profound interest in leveraging data analytics to address complex challenges in the financial sector.

This YouTube channel serves as both a platform for sharing knowledge and a personal journey of continuous learning. With a commitment to growth, I aim to expand my skill set by publishing 2 to 3 new videos each week, delving into various aspects of data analytics/science and Artificial Intelligence. Join me on this exciting journey as we explore the endless possibilities of data together.

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Hey guys I hope you enjoyed the video! If you did please subscribe to the channel!


*Both Datacamp and Stratascratch are affiliate links.

RyanAndMattDataScience
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this needs more views. was so in depth and perfect for a beginner!

KyaBroderick
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I loved the walkthrough, honestly the last about 35 mins I had no idea what was going on but it's really cool that people like you are giving free tutorials on such complex work. Thanks!

collingreens
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Hope you enjoyed this video, it took so long to produce. If you enjoyed it, please subscribe to the channel.
I just uploaded the 2nd part of this video where I improve the model (linked down below)

Below are a few links that you should check out:


RyanAndMattDataScience
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It was a super useful video and I am happy to have done my first Data Science project. Thank you very much.

AmaRan
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Thank you for this, your videos are so helpful. Keep it up!

yakosti
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So helpful !! Ideal demonstration for my first projects, going forwards

autiematic
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I got 78% result using forest. Thanks for the brilliant explanation!

aviluminos
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at least you explain in detail what you are typing for after copy your line of code. Nice video btw

ChillWebDeveloper
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yes man, much appriciated for your efforts

ritamchatterjee
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Excellent video. So much in it, thought process, code tips etc.

robertbenson
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Hi, great video. One idea — instead of writing out so many loc statements, it might be easier to just use labels=False when using qcut.

idontevenwanttomakea
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you explained it in fantastic way just one request
will you please provide the valid link for notebook actually its not working

katorechaitanya
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Very cool video! Would love to see some of this type of content.

samallen
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Hi Ryan, I am new to data science. I am a bit lost on what the point of analyzing the ticket number and passenger name. What is the goal of doing that? Same with qcuts, are we doing them to help with a decision tree model? Do we need to do any of this if we just build a regression model?

jacksun
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quick question: does Kaggle give you a rating based on speed/efficiency? I'm wondering specifically about just importing the whole libraries.

Orokusaki
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Extremely interesting tutorial, learnt a lot of new functions in pandas and different ways to analyze the date. Thanks Ryan !!😀

John-xiim
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Just a suggestion your next video should be on using chatgbt for this project

tosinwilliams
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Thanks... I really enjoyed and you explain so well.... Bless you.

elfincredible
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Hi @Ryan Thanks for making this amazing video. I just want to understand why did use "Plus one for yourself" @25:05? Thank you!

AbelGriffen