All you need to know about Kaggle | What is Kaggle | Kaggle Competitions | Great Learning

you might have heard of this website called as kaggle but wouldn't know what exactly it is or you would have been told by your professors or peers to check this site if you want to improve your data science skills so this tutorial is dedicated especially to that it will help you understand what exactly is kaggle and how can kaggle help you in improving your data science expertise now before we go ahead please do subscribe to great learnings youtube channel and click on the bell icon so that you get a notification of our upcoming videos also i'd like to inform you guys that we have launched a completely free platform called as great learning academy where you have access to free courses such as ai cloud and digital marketing you can check out the details in the description below so i've opened up kaggle.com over here this is the home page of kaggle.com and as you see we've got these uh five primary tabs over here and we will start off with this compete tab so competitions on kaggle is what actually makes this site so amazing so you have all of these competitions over here active completed and in class if you look at these competitions you would see that there's a prize money as well so if you actually win this competition you have a chance to win hundred thousand dollars similarly you have this competition over here jane street market prediction and if you win this you again have a chance to win hundred thousand dollars and the best part is it's not necessary that you would have to participate by yourself you can also participate as a team so you can collaborate with your friends or your professors and participate in this competition and well if you're the best well you can win this huge amount of money now one thing to actually note over here is all of these competitions are extremely difficult where you have this huge prize money so as you see over here this competition had started a month ago and still you do not have a winner this competition over here had started three months ago and still you do not have a winner so these competitions where you have this huge prize money these competitions are participated by data scientists and ml practitioners who have more than 10 plus years of experience and uh you know they would want to uh show their skills in this competition over here but that shouldn't scare you if you are a newbie because kaggle provides you competitions with different ranges so you have easy competitions you have intermediate competitions you also have these tough competitions with huge prize money so as a beginner if you would want to just improve your skills then you have a lot of competitions for you as well and the best competition to start is this titanic competition so as you see over here if you're new to kaggle then just start off with this titanic competition click on this link and as you see this is the titanic competition which most of the beginners start off with now before actually starting the competition go through the rules understand what the rules say then you can join the competition and to actually join this you would have to sign in first you'd have to create your account on kaggle then you can join over here now this is the competitions and later on we'll also see how to join a competition and uh submit your result but for now let's also explore other tabs so we've looked at competitions now let's see what this data sets tab is about so the world is inundated with data so whatever you do generates data if you upload a picture on facebook that generates data if you upload a video on youtube that generates data if you make a credit card transaction that also generates data so now since everything generates data you have data related to every single field and on kaggle i'm pretty sure that you will be able to find data sets with respect to almost everything so here in this tab either you can create your own public data set or you can work on other public data sets which are already present so as you see over here you have all of these data sets you have your selection 2020 code 19 data from john hopkins university u.s election 2020 tweets and so on now let me actually open up this data set user selection 2020 and as you see here this is a cc0 data set cc 0 means that this is available for all now let's look at all of the columns which are there so this tells you about the governors from a particular county so general information about reporting words to governor raised by county and you have these columns over here state name county name reporting words total votes and word percent so you can just perform your expiratory data analysis or implement your ml algorithms on this data set and learn what is actually there in this data now let me actually show you why this tab is extremely interesting as i've told you you can find data sets with respect to almost everything so let's say i'm a huge fan of fifa so if i'd want to work on a fifa data set i will just type in fifa over here and you would see that i have a lot of data sets related to fifa similarly let's say if you watch a lot of tv series i'm pretty sure that you would have seen game of thrones and you'd want to work on game of thrones data just type in game of thrones over here and you have again a lot of data sets related to game of thrones now let's say if you're into gaming and if you play this game called as pubg you see that there are also a lot of data sets related to pubg so whatever field interests you you can pick up that particular data and start working on it now let's head on to the next tab which is notebooks so notebook says where you find notebook submitted by other people what is a notebook notebook is basically code submitted by other people now it's not necessary that you can only look at the code submitted by other people you can also work by yourself on kaggle itself so first i'll actually show you let me actually go back to this data tab over here and let me open up some notebook related to fifa so here i have this fifa 20 complete player data set now when i open this up i have this notebooks tab again and here you would see that a lot of people would have submitted their code so this person over here has submitted a code which is about fifa data analysis and visualization let me just open this up and let's see what is there so here you would see that this person has mostly done data manipulation and data visualization now if you want to see the result and if you would also want to look at the code you can find both of them so here this person is just loading up the required libraries then he's having a glance at the data so here you would see that this person has created this beautiful plot over here and you'll be able to find the code for almost everything right so if you want to understand how this person has implemented the code or how this person has implemented this visualization just go through this person's code and you will you'll be able to learn more of r or python from other people's notebooks over here and as i have told you it's not necessary that you can only go through other people's code you can work by yourself as well so let me open up this notebooks tab again and i will click on this new notebook tab and here you would see that so some folks who are new to programming or new to machine learning in general would have a problem in installing python into their systems or would have a problem in installing python related ids into their systems so for that purpose you can just directly head on to this page and start writing your code let me just write a simple code for you folks over here i'll write down print hello i'll hit on this button and you would see that i have written my piece of code so let's say if you're unable to install python or if you are unable to work with any of the python ids you can just head over here and start working with your code as simple as that then you also have a lot of communities over here so the best part about communities is let's say as a beginner if you want to learn something or discuss something if some field interests you you have all of these different communities so you have computer vision nlp data visualization neural networks tensorflow and so on then you also have something called as courses so for someone who is a total total newbie and uh wouldn't know anything about python or machine learning or data visualization or any of these topics you can just go ahead and start learning so let's say if you want to learn natural language processing just open this up over here and you would see that you have this entire course related to natural language processing so i'll open this up intro to nlp and you would see that you have all of this uh tutorial related to nlp so this is how you can check these courses and improve your skills with respect to all of these different courses and now we will go back to where we started let's actually see how to join our first competition so let me open up my kaggle home page over here so i already have an account on kaggle i'll go to the home page let me actually go to the compete page over here and i will click on titanic which should be the easiest competition that you can participate in on kaggle and here you look at the rules then you understand what the problem statement is about so here you see that you have this description and you have the challenge so 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 which are name age gender socioeconomic class and so on so this is these are the rules which would have to know you'd have to join the competition first you'd have to write your code then make a submission and once you submit your code you can check your leaderboard standings so here as you see i had already participated in this and i have some of my submissions over here so this was long long time ago as you see so these were some of the submissions i had made and uh this was four years ago and i had a public score of 0.79 so if you have to submit all you have to do is click on submit predictions and as you see over here click over here and then you just have to select your public file and upload it right over here and then you'll be able to see how you are performing so folks this was all about kaggle where you can participate in different data science competitions you can work on different public data sets you can also explore other notebooks and you can also learn for free about different topics so folks this brings us to the end of this tutorial i hope this would have helped you to understand the bit of kaggle and get started with your competition on kaggle now before i actually sign off i'd like to again inform you about great learning academy where you have courses related to data science artificial intelligence and a lot lot more and once you complete these courses you will get a course completion certificate so you can find the link of great learning academy in the description below so folks thank you very much and have a great learning ahead you

Channel: Great Learning

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Keywords: Great Learning, Great Lakes, Data science, Kaggle, kaggle for beginners, kaggle free courses, kaggle tutorial, kaggle tutorial for beginners, Kaggle competition, kaggle competitions for beginners, Kaggle projects, Kaggle projects for beginners, learn kaggle, kaggle explained, kaggle data science projects, kaggle data science, kaggle projects machine learning, kaggle titanic python

Id: jbRNGuz3IRM

Length: 13min 25sec (805 seconds)

Published: Mon Nov 30 2020