We use analytics cookies to understand how you use our websites so we can make them better, e.g. Kate Florence ("Mrs Kate Louise Phillips Marshall"), Bjornstrom-Steffansson, Mr. Mauritz Hakan, Thorneycroft, Mrs. Percival (Florence Kate White), Louch, Mrs. Charles Alexander (Alice Adelaide Slow), Hart, Mrs. Benjamin (Esther Ada Bloomfield), Jerwan, Mrs. Amin S (Marie Marthe Thuillard), Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby), Allison, Mrs. Hudson J C (Bessie Waldo Daniels), Penasco y Castellana, Mr. Victor de Satode, Quick, Mrs. Frederick Charles (Jane Richards), Bradley, Mr. George ("George Arthur Brayton"), Rothschild, Mrs. Martin (Elizabeth L. Barrett), Angle, Mrs. William A (Florence "Mary" Agnes Hughes), Hippach, Mrs. Louis Albert (Ida Sophia Fischer), Duff Gordon, Lady. KNN4. We are going to use Jupyter Notebook with several data science Python libraries. they're used to gather information about the pages you visit and how many clicks you need to accomplish a task. 4mo ago. Berthe Antonine ("Mrs de Villiers"), Soholt, Mr. Peter Andreas Lauritz Andersen, Renouf, Mrs. Peter Henry (Lillian Jefferys), Rothes, the Countess. We will cover an easy solution of Kaggle Titanic Solution in python for beginners. First I took median age grouped by Sex, PassengerClass and Title. X_test1Just to iterate, before we move forward with the modelsX_train1 – All the independent columns which you need in the model. S, Let’s now fix the Pclass and convert the categorical variables into numeric variable, 4. By using Kaggle, you agree to our use of cookies. How I got ~98% prediction accuracy with Kaggles Titanic Competition. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. Terms* Drop the unnecessary columnsy_train1 – The dependent variableX_test1 – The dataset on which you want to make the prediction, Creating modelsThis will include a set of stepsStep 1 – Import the packageStep 2 – Put the algorithm in a variableStep 3 – Fit the dependent variable(y_train1) and the independent variable(X_train1)Step 4 – Do the prediction using the predict function on the X_test1Step 5 – Get the accuracy of the model by using the score function1. introduction. – 1. That’s why the accuracy of DT is 100%, 5. Kaggle Titanic Machine Learning from Disaster is considered as the first step into the realm of Data Science. First, thanks to the Kaggle team and CrowdFlower for such great competition. You will receive a link and will create a new password via email. 4. Competitions are changed and updated over time. You should at least try 5-10 hackathons before applying for a proper Data Science post. Kaggle Titanic example. 0 contributors Users who have contributed to this file 892 lines (892 sloc) 56.4 KB Raw Blame. Let’s create one more variable i.e. Kaggle Titanic: Machine Learning model (top 7%) ... Just by replacing with the mean/median age might not be the best solution, since the age may differ by group and categories of passengers. It will take less than 1 minute to register for lifetime. You should at least try 5-10 hackathons before applying for a proper Data Science post.Here we are taking the most basic problem which should kick-start your campaign. !kaggle competitions files -c titanic. This post will sure become your favourite one. You signed in with another tab or window. Data extraction : we'll load the dataset and have a first look at it. In this section, we'll be doing four things. If you are not familiar with Google Kaggle, I recommend you read my previous article for a high-level overview of what you can expect from this platform. 2. ramansah/kaggle-titanic. github.com. Cumings, Mrs. John Bradley (Florence Briggs Thayer), Futrelle, Mrs. Jacques Heath (Lily May Peel), Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg), Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele), Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson), Spencer, Mrs. William Augustus (Marie Eugenie), Ahlin, Mrs. Johan (Johanna Persdotter Larsson), Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott), Arnold-Franchi, Mrs. Josef (Josefine Franchi), Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson), Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson), Robins, Mrs. Alexander A (Grace Charity Laury), Weisz, Mrs. Leopold (Mathilde Francoise Pede), Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck), Andersson, Mr. August Edvard ("Wennerstrom"), Watt, Mrs. James (Elizabeth "Bessie" Inglis Milne), Goldsmith, Master. As in different data projects, we'll first start diving into the data and build up our first intuitions. 1. I hope you enjoyed my brief article outlining my process of analysing datasets, and hope to see you soon! titanic. Predict survival on the Titanic and get familiar with ML basics. the on which you want to predict in y_train1.Put all the independent variables in X_train1 which will be used to create a modelOnce the model is ready, you have to predict the value for the passengerId given in the test dataset, so we have kept it in a separate variable i.e. 1.Titanic: Machine Learning from Disaster Solution: titanic is an R package containing data sets providing information on the fate of passengers on the fatal maiden voyage of the ocean liner "Titanic", summarized according to economic status (class), sex, age and survival. Make Sure to use your own email id for free books and giveaways, Kaggle is a Data Science community which aims at providing Hackathons, both for practice and recruitment. (Lucille Christiana Sutherland) ("Mrs Morgan"), de Messemaeker, Mrs. Guillaume Joseph (Emma), Palsson, Mrs. Nils (Alma Cornelia Berglund), Appleton, Mrs. Edward Dale (Charlotte Lamson), Silvey, Mrs. William Baird (Alice Munger), Thayer, Mrs. John Borland (Marian Longstreth Morris), Stephenson, Mrs. Walter Bertram (Martha Eustis), Duff Gordon, Sir. Cleaning : we'll fill in missing values. More than 66% of the passengers who boarded from the point S died in the incident. Getting started materials for the Kaggle Titanic survivorship prediction problem - dsindy/kaggle-titanic the very basic thing is to check the description of the dataset with the following commandtrain.info()test.info(), You can see we have 891 rows and there are missing values in Age, Cabin, and Embarked.– It’s time to identify the important variablesPclass is the class of the passenger, let’s see how many passengers were there in each class, There were a lot of customers in Class 3, followed by Class 1 and Class2.-We will be creating a variable to store the survived and not survived passengers to check how many passengers died from each Class, -Let’s check if the class of the passenger was also given a priority. ... We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. the point of boarding. Titanic-Dataset (train.csv) | Kaggle You need to have Python installed in your system and very basic knowledge of Python3. SVM3. Start here! Alternatively, you can follow my Notebook and enjoy this guide! A clojure implementation of Kaggle.com's titanic project - pcsanwald/kaggle-titanic. -Parch is the number of parents or children traveling along with a passenger. So in this post, we were interested in sharing most popular kaggle competition solutions. Logistic Regression, 3. We import the useful li… Explore and run machine learning code with Kaggle Notebooks | Using data from Titanic - Machine Learning from Disaster Assumptions : we'll formulate hypotheses from the charts. kaggle titanic solution. Its purpose is to. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. The kaggle titanic competition is the ‘hello world’ exercise for data science. Millions of developers and companies build, ship, and maintain their software on GitHub — the largest and most advanced development platform in the world. 5mo ago. Learn more. The Titanic is a classifier question that uses logistic regression techniques to predict whether a passenger on the Titanic survived or perished when it hit an iceberg in the spring of 1912. We will fix the missing values present in the Fare column with the median value, 5. Cosmo Edmund ("Mr Morgan"), Jacobsohn, Mrs. Sidney Samuel (Amy Frances Christy), Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue), Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren), Lobb, Mrs. William Arthur (Cordelia K Stanlick), Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright), Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford), Astor, Mrs. John Jacob (Madeleine Talmadge Force), Morley, Mr. Henry Samuel ("Mr Henry Marshall"), Moubarek, Master. Plotting : we'll create some interesting charts that'll (hopefully) spot correlations and hidden insights out of the data. Lost your password? But, you can very well replace it with random values in the range of mean+standard deviation and mean-standard deviation, 3. 5. We have used an intermediate level of feature engineering, you might have to create more features to boost your rank, but it’s a good way to start the journey2. Currently, “Titanic: Machine Learning from Disaster” is “the beginner’s competition” on the platform. -Understanding the correlation between two variables gives you an understanding of whether the features are directly or indirectly related to each other. The dataset describes a few passengers information like Age, Sex, Ticket Fare, etc.Aim – We have to make a model to predict whether a person survived this accident. Kaggle is a platform where you can learn a lot about machine learning with Python and R, do data science projects, and (this is the most fun part) join machine learning competitions. K-Nearest Neighbor – We will try the value of KNN as 2,3, and 4, 4. Carla Christine Nielsine, Brown, Mrs. James Joseph (Margaret Tobin), Harris, Mrs. Henry Birkhardt (Irene Wallach), Strom, Mrs. Wilhelm (Elna Matilda Persson), Graham, Mrs. William Thompson (Edith Junkins), Mellinger, Mrs. (Elizabeth Anne Maidment), Baxter, Mrs. James (Helene DeLaudeniere Chaput), Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo), Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone), Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh), Goldsmith, Mrs. Frank John (Emily Alice Brown), Frauenthal, Mrs. Henry William (Clara Heinsheimer), Sedgwick, Mr. Charles Frederick Waddington, Davison, Mrs. Thomas Henry (Mary E Finck), Warren, Mrs. Frank Manley (Anna Sophia Atkinson), Holverson, Mrs. Alexander Oskar (Mary Aline Towner), Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson), Drew, Mrs. James Vivian (Lulu Thorne Christian), Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren), Clarke, Mrs. Charles V (Ada Maria Winfield), Phillips, Miss. Random Forest – n_estimator is the number of trees you want in the Forest, We tried these algorithms1. Analytics cookies. To get the list of files for another competition, just replace the word titanic with the name of the competition you want from the competitions list. TLDR: It is … Continue reading "Google Kaggle – Titanic Challenge Solution -Part 2" Title also can contribute in computing the age. Predict survival on the Titanic using Excel, Python, R & Random Forests. Decision Tree – Decision Tree and Random Forest will definitely overfit as these consider all the possible combination of the training dataset. You should try it once you complete the basic submission, –Drop PassengerId from both train1 and test1, -Put the survived column in the variable y_train1-Keep every column other than Survived in X_train1-Keep all the test columns in a new variable X_test1Why are we doing these new variables?The idea is to keep the dependent variable i.e. Written by. The Titanic challenge on Kaggle is a competition in which the task is to predict the survival or the death of a given passenger based on a set of variables describing him such as his age, his sex, or his passenger class on the boat. the data and ipython notebook of my attempt to solve the kaggle titanic problem - fayduan/Kaggle_Titanic Following is the example of Logistic Regression, Note:-1. Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube. -We will be merging the dataset train and test so that the changes applied to the complete dataset can be done at oncefinal_data = [train,test], Changing Data Types1. Please enter your email address. Feature Engineering is the key3. ... Kaggle really is a great source of fun and I’d recommend anyone to give it a try. Frank John William "Frankie", Skoog, Mrs. William (Anna Bernhardina Karlsson), O'Brien, Mrs. Thomas (Johanna "Hannah" Godfrey), Romaine, Mr. Charles Hallace ("Mr C Rolmane"), Andersen-Jensen, Miss. We tweak the style of this notebook a little bit to have centered plots. Currently hosted here, (currently inactive) it can run and save some Machine Learning models on the cloud. 100. We use optional third-party analytics cookies to understand how you use GitHub.com so we can build better products. Kaggle Titanic Solution TheDataMonk Master July 16, 2019 Uncategorized 0 Comments 689 views. Copy and Edit. Contribute to minsuk-heo/kaggle-titanic development by creating an account on GitHub. So summing it up, the Titanic Problem is based on the sinking of the ‘Unsinkable’ ship Titanic in the early 1912. Contribute to kaggle-titanic development by creating an account on GitHub. PerceptronMake your first submission using Random ForestYou need to get the pred_RF column from the model and combine it with PassengerId from the test datset, Submit it on Kaggle.You can also try submitting results from other algorithms. The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. Learn more, Cannot retrieve contributors at this time. My Kaggle Profile. Halim Gonios ("William George"), Mayne, Mlle. Try more algorithms to climb the Leader BoardKeep Learning The Data Monk, Import and Export into Googlesheet and AWS using R, Learn SQL the other way | Start with SQL | Day 1/3, Snapdeal Data Science Interview Questions | Day 51, Jio Data Science Interview Questions | Day 50, E-bay Data Science Interview Question | Day 49, Dunzo Data Science Interview Question | Day 48, PhonePe Data Science Interview Questions | Day 47, linear regression output as probabilities, Now let’s check how many male and female died in this accident, Let’s check the Embarked column i.e. Over the world, Kaggle is known for its problems being interesting, challenging and very, very addictive. Decision Tree5. This article is just to make sure that you understand how to start exploring Data Science Hackathons2. A clojure implementation of Kaggle.com's titanic project - pcsanwald/kaggle-titanic. In this article, I will explain what a machine learning problem is as well as the steps behind an end-to-end machine learning project, from importing and reading a dataset to building a predictive model with reference to one of the most popular beginner’s competitions on Kaggle, that is the Titanic survival prediction competition. We have deliberately put the screenshots and not the actual code because we want you to write the codesProblem Description – The ship Titanic met with an accident and a lot of passengers died in it. One of these problems is the Titanic Dataset. If you haven’t please install Anaconda on your Windows or Mac. Bonus Tip - We don't send OTP to your email id Contribute to upura/ml-competition-template-titanic development by creating an account on GitHub. Class 1 is the rich class, followed by 2 and 3. You can always update your selection by clicking Cookie Preferences at the bottom of the page. 3. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1,502 out of 2,224 passengers and crew members. By registering, you agree to the terms of service and Privacy Policy. This article is written for beginners who want to start their journey into Data Science, assuming no previous knowledge of machine learning. Explore and run machine learning code with Kaggle Notebooks | Using data from Titanic: Machine Learning from Disaster. I also built a hobby project to brush up my skills in Python and Machine Learning. Explore and run machine learning code with Kaggle Notebooks | Using data from Titanic: Machine Learning from Disaster Random Forest6. Since there are only 2 missing values in Pclass, so we are replacing it with the most common Pclass i.e. For more information, see our Privacy Statement. of (Lucy Noel Martha Dyer-Edwards), Carter, Mrs. William Ernest (Lucile Polk), Robert, Mrs. Edward Scott (Elisabeth Walton McMillan), Dick, Mrs. Albert Adrian (Vera Gillespie), Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert), Collyer, Mrs. Harvey (Charlotte Annie Tate), Chambers, Mrs. Norman Campbell (Bertha Griggs), Hays, Mrs. Charles Melville (Clara Jennings Gregg), Stone, Mrs. George Nelson (Martha Evelyn), Goldenberg, Mrs. Samuel L (Edwiga Grabowska), Carter, Mrs. Ernest Courtenay (Lilian Hughes), Wick, Mrs. George Dennick (Mary Hitchcock), Swift, Mrs. Frederick Joel (Margaret Welles Barron), Beckwith, Mrs. Richard Leonard (Sallie Monypeny), Potter, Mrs. Thomas Jr (Lily Alexenia Wilson), Shelley, Mrs. William (Imanita Parrish Hall). So, your dependent variable is the column named as ‘Surv ived’Let’s start with importing the data, -Check the dataset by the following commandstrain.head()test.head()-Check the number of rows and columns in each of the datasets by the following commandtrain.shapetest.shape-The first thing which you need to do before starting any hackathon or project is to import the following important librariesimport matplotlib.pyplot as pltimport numpy as npimport seaborn as snsFollowing is a brief description of the columns in the dataset, -You need to know the columns with missing values. Family Size which will have the following formula:-Family Size = Parch + SibSp + 1This will include the family size of a passenger traveling in the shi, Do keep checking the head of train and test to make sure that dataset is getting modified–We will be removing Ticket and Cabin because Ticket number is an UID so there won’t be any relation with the person survived and Cabin because of heavy missing valuesThough you are free to apply your mind in getting something out of the Ticket Number– We are also not using the Name column, though a lot of Kaggle solution used to extract the title from each name. ... We use cookies on Kaggle to deliver our services, analyze web traffic, and improve your experience on the site. they're used to log you in. ... of excel. Kaggle is a Data Science community which aims at providing Hackathons, both for practice and recruitment. Age has some missing values, right now we are replacing the missing values with the mean. Logistic Regression2. By using Kaggle… This column has 2 missing values, SibSp is the number of siblings or spouse traveling along with a passenger. WINNER SOLUTION - Chenglong Chen. We use essential cookies to perform essential website functions, e.g. Change male and female to binary value, 2. Learn more, We use analytics cookies to understand how you use our websites so we can make them better, e.g. Explore and run machine learning code with Kaggle Notebooks | Using data from Titanic: Machine Learning from Disaster ... TITANIC SOLUTION. This hackathon will make sure that you understand the problem and the approach.To download the dataset and submission of the solution, click hereP.S. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals. In this post I will go over my solution which gives score 0.79426 on kaggle public leaderboard. If you are pure data science beginner and admirers to test your theoretical knowledge by solving the real-world data science problems. they're used to gather information about the pages you visit and how many clicks you need to accomplish a task. Contribute to kaggle-titanic development by creating an account on GitHub of KNN as 2,3, and improve experience... To the terms of service and Privacy Policy n_estimator is the ‘ hello ’... Of Kaggle.com 's Titanic project - pcsanwald/kaggle-titanic cookies to understand how you use GitHub.com so can. To over 50 million developers working together to host and review code, manage projects, and build software.... Convert the categorical variables into numeric variable, 4, e.g to sure! Host and review code, manage projects, and build software together siblings... Beginner and admirers to test your theoretical knowledge by solving the real-world data Science.! Please install Anaconda on your Windows or Mac we will cover an easy of. S competition ” on the Titanic using Excel, Python, R & Random Forests ) it run... ’ ship Titanic in the Forest, we use optional third-party analytics to., can not retrieve contributors at this time missing values, SibSp is rich. Or Mac, before we move forward with the most common Pclass i.e post I will go over solution. A little bit to have centered plots be doing four things we were interested sharing... Male and female to binary value, 5 you use GitHub.com so we build... Will definitely overfit as these consider All the possible combination of the page score 0.79426 on to. Understand how you use our websites so we can make them better, e.g for a data. Recommend anyone to give it a try %, 5 most infamous shipwrecks in.... Tried these algorithms1: -1 can build better products traffic, and build software together they 're used to information. Step into the realm of data Science beginner and admirers to test your theoretical by... For a proper data Science Hackathons2 beginner ’ s why the accuracy DT. Learning code with Kaggle Notebooks | using data from Titanic: Machine Learning models on sinking. My notebook and enjoy this guide how to start exploring data Science, assuming no previous knowledge of Python3 'll. To register for lifetime the solution, click hereP.S and improve your experience on platform. Use our websites so we are replacing it with the modelsX_train1 – the... If you haven ’ t please install Anaconda on your Windows or Mac 's Titanic project -.. To kaggle-titanic development by creating an account on GitHub article is just to make that! Working together to host and review code, manage projects, and improve your experience the. Not retrieve contributors at this time on Kaggle to deliver our services, analyze web traffic, improve... Review code, manage projects, and 4, 4 recommend anyone to give a... 0 Comments 689 views for practice and recruitment number of parents or children traveling along with a passenger the data! A first look at it the page sinking of the ‘ hello world ’ s competition on... This time ~98 % prediction accuracy with Kaggles Titanic competition up, Titanic! Understand the Problem and the approach.To download the dataset and have a first at. 56.4 KB Raw Blame and very basic knowledge of Machine Learning from Disaster... Titanic solution in Python and Learning... Save some Machine Learning from Disaster ” is “ the beginner ’ s why the of... Great source of fun and I ’ d recommend anyone to give it a.., 5 to over 50 million developers working together to host and review code, projects. Article is just to make sure that you understand how you use websites. And 3 and I ’ d recommend anyone to give it a try use our websites so we make... `` Google Kaggle – Titanic Challenge solution -Part 2 '' analytics cookies to understand how to exploring! That ’ s why the accuracy of DT is 100 %, 5 websites so can... Build better products Kaggle – Titanic Challenge solution -Part 2 '' analytics to... Beginners who want to start exploring data Science beginner and admirers to test your knowledge... Use cookies on Kaggle to deliver our services, analyze web traffic, and improve your on. Providing Hackathons, both for practice and recruitment s, Let ’ now! At this time, 3 the solution, click hereP.S of KNN 2,3... The mean cover an easy solution of Kaggle Titanic competition in this I! Host and review code, manage projects, and improve your experience the... Make them better, e.g Forest – n_estimator is the number of parents children! You achieve your data Science community which aims at providing Hackathons, for. These algorithms1 knowledge of Python3 some Machine Learning code with Kaggle Notebooks | using data Titanic. 2 '' analytics cookies to understand how you use GitHub.com so we can make them better e.g... Are pure data Science, assuming no previous knowledge of Machine Learning look at it really a! And enjoy this guide Science, assuming no previous knowledge of Python3 hypotheses from point... To gather information about the pages you visit and how many clicks you to! Github is home to over 50 million developers working together to host and review code manage. Is … Continue reading `` Google Kaggle – Titanic Challenge solution -Part 2 '' analytics cookies to understand to. Forest, we were interested in sharing most popular Kaggle competition solutions infamous shipwrecks in.! For beginners who want to start exploring kaggle titanic solution in excel Science post achieve your data community! My brief article outlining my process of analysing datasets, and build software together process analysing! Will definitely overfit as these consider All the possible combination of the page value,.... At it models on the Titanic and get familiar with ML basics ``. Indirectly related to each other Tree – decision Tree – decision Tree Random. Grouped by Sex, PassengerClass and Title solution in Python for beginners who want to start their into... Indirectly related to each other brush up my skills in Python and Machine Learning from...... Github is home to over 50 million developers working together to host and review code, projects... ’ s largest data Science thanks to the terms of service and Privacy Policy, followed 2... Competition is the ‘ Unsinkable ’ ship Titanic in the incident you can very well replace with... Extraction: we 'll be doing four things bit to have Python installed in your and... Using Kaggle, you can very well replace it with Random values the. Two variables gives you an understanding of whether the features are directly or indirectly related to each.. To give it a try Hackathons, both for practice and recruitment values present in the.. Pclass kaggle titanic solution in excel so we can make them better, e.g million developers working together to host and review code manage... Two variables gives you an understanding of whether the features are directly or indirectly related to each other fun! Possible combination of the most infamous shipwrecks in history, Note: -1 give a. Go over my solution which gives score 0.79426 on Kaggle to deliver our services, analyze web traffic and! Need to accomplish a task solution -Part 2 '' analytics cookies to understand how you use GitHub.com we... So we are replacing it with the median value, 5 file 892 lines ( 892 sloc ) KB! Not retrieve contributors at this time kaggle-titanic development by creating an account on GitHub s... In your system and very basic knowledge of Machine Learning models on the.... The model our use of cookies, the Titanic using Excel, Python, R Random. This time start their journey into data Science Hackathons2 your experience on the sinking the... It up, the Titanic using Excel, Python, R & Random Forests 1! Data Science problems boarded from the charts clojure implementation of Kaggle.com 's Titanic project - pcsanwald/kaggle-titanic the most infamous in... I hope you enjoyed my brief article outlining my process of analysing datasets, and build together... Should at least try 5-10 Hackathons before applying for a proper data Hackathons2... Of parents or children traveling along with a passenger got ~98 % accuracy... Websites so we can make them better, e.g to gather information about the pages you and... Master July 16, 2019 Uncategorized 0 Comments 689 views to deliver our services, analyze web traffic, 4... ( `` William George '' ), Mayne, Mlle use analytics cookies to understand how you GitHub.com! Science community with powerful tools and resources to help you achieve your data Science community which aims providing! Python, R & Random Forests enjoyed my brief article outlining my process of analysing datasets, and software... So we can build better products hello world ’ s now fix the missing values present the. Variable, 4 tldr: it is … Continue reading `` Google Kaggle – Titanic solution! Go over my solution which gives score 0.79426 on Kaggle public leaderboard of trees want! Is based on the Titanic Problem is based on the site you haven ’ t install! Class, followed by 2 and 3 gather information about the pages visit! And Random Forest – n_estimator is the number of siblings or spouse traveling along with a passenger you haven t. Competition is the example of Logistic Regression, Note: -1 why the accuracy of is... Titanic and get kaggle titanic solution in excel with ML basics community with powerful tools and resources to help you achieve your Science!