Titanic Survival prediction : from Analysis to Application 🚢 || End to End project
Hello Guys,
In this video, we'll Dive into the mystery of the Titanic disaster with our groundbreaking machine learning project! We analyze the Titanic survival dataset, revealing hidden insights into the factors influencing who lived and who perished.
📊 Exploratory Data Analysis: Witness the power of data visualization as we uncover the impact of passenger class, gender, age, and embarkation point on survival rates through captivating seaborn countplots.
🧠 Predictive Modeling: Using state-of-the-art logistic regression techniques, we craft a predictive model capable of forecasting survival probabilities based on individual passenger attributes.
📈 Model Evaluation: Join us as we meticulously evaluate the model's accuracy on both training and testing datasets, ensuring its robustness and reliability.
🌐 Interactive Streamlit Web App: Experience the magic firsthand! Our intuitive Streamlit web application empowers users to input passenger details and receive instant survival predictions, bringing the Titanic story to life in real-time.
🚀 Don't miss out on this captivating voyage through the realm of predictive analytics. Join us as we unravel the mysteries of the Titanic disaster and ignite your passion for data science!
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💻 Source Code:
refer EP-73.py and EP-74.py of this repo
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