How do I start the kaggle Titanic problem?

Starts here6:37How to Get Started with Kaggle’s Titanic Competition – YouTubeYouTubeStart of suggested clipEnd of suggested clip47 second suggested clipThere you need to get the data so the data is going to be under the data tab on the competition pageMoreThere you need to get the data so the data is going to be under the data tab on the competition page which is the same place you went to to join the competition in the first place.

How do I raise my score in Titanic kaggle?

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1. First of all, good job!
2. Looking at your code, I found you are using the modern keras package for bad-ass neural networks.
3. More important than choosing the right algorithm is cleaning your data I think.
4. Did you do any kind of validation / cross-validation?

Is kaggle Titanic data Real?

Is the data real? The data is real and something suspicious happened with the Titanic..

What is titanic problem?

So summing it up, the Titanic Problem is based on the sinking of the ‘Unsinkable’ ship Titanic in the early 1912. It gives you information about multiple people like their ages, sexes, sibling counts, embarkment points and whether or not they survived the disaster.

What is parch in Titanic dataset?

parch – Number of Parents/Children Aboard. ticket – Ticket Number. fare – Passenger Fare. cabin – Cabin.

What is p class in Titanic?

pclass refers to passenger class (1st, 2nd, 3rd), and is a proxy for socio-economic class. Age is in years, and some infants had fractional values.

What is a good titanic score?

Titanic leaderboard: a score > 0.8 is great!

Which model is best for Titanic dataset?

So, the logistic regression model still seems to be the best model. It is a simple and easy to use model and the accuracy of 81.5 is a pretty good score for the Titanic dataset.

What is Titanic survival prediction?

Our model predicts 81\% of the time, a passengers survival correctly (precision). The recall tells us that it predicted the survival of 73 \% of the people who actually survived.

How do you fill missing values in the Titanic dataset?

How to fill NaN values by imputation, in the Titanic Age column

1. Compute mean of each Pclass/Sex group in the training set.
2. Map all NaN values in the training set to the right mean.
3. Map all NaN values in the test set to the right mean (lookup by Pclass/Sex and not based on indices)