Building a Machine Learning App with Streamlit: Can You Predict Survival on the Titanic?

🚢The Titanic was one of the worst nautical disasters in history, but we can use machine learning to predict survival.

⚙️In this episode, we build a machine learning app with Streamlit and scikit-learn in a short time frame.

🔢We collect various features like passenger ID, class, name, gender, age, and more to make predictions.

✅The app makes predictions and shows whether a passenger would survive or not.

👎If we don't meet the time limit or make errors, there's a challenge with a $50 Amazon gift card for you!

Can we really predict survival on the Titanic?

—Yes, using machine learning models, we can analyze various features to predict survival with a certain degree of accuracy.

What programming language and libraries did you use?

—We used Python and libraries like Streamlit and scikit-learn to build the machine learning app.

What features did you consider in the prediction?

—We considered features like passenger ID, class, name, gender, age, number of siblings, fare amount, cabin, and the embarkation point.

Can I try the app myself?

—Yes, you can try the app by running the code provided in the video. You can input various features and see the prediction.

What happens if the time limit is not met or errors are made?

—If the time limit is not met or errors are made, there's a challenge with a $50 Amazon gift card for the first person to claim it.

00:00The Titanic disaster was a major event, but we can use machine learning to predict survival.

02:59We start building the machine learning app using Streamlit and scikit-learn.

05:17We set up various features like passenger ID, class, name, gender, age, and more.

08:21We add a predict button to make predictions based on the input features.

10:54We run the app and demonstrate how to make predictions.

11:58We wrap up the video and mention the challenge with a $50 Amazon gift card.