Calculate survival probability based on passenger details
Visualize model performance on function calling tasks
Create and manage ML pipelines with ZenML Dashboard
Evaluate AI-generated results for accuracy
Measure execution times of BERT models using WebGPU and WASM
Text-To-Speech (TTS) Evaluation using objective metrics.
Compare model weights and visualize differences
Compare and rank LLMs using benchmark scores
Calculate GPU requirements for running LLMs
Evaluate RAG systems with visual analytics
Calculate VRAM requirements for LLM models
Convert Hugging Face model repo to Safetensors
Demo of the new, massively multilingual leaderboard
Titanic Survival in Real Time is a cutting-edge tool designed to analyze and predict survival probabilities for passengers aboard the RMS Titanic based on their personal details. This application leverages advanced machine learning models to simulate real-time survival predictions, making it an invaluable resource for researchers, historians, and enthusiasts interested in the Titanic's tragic history.
What models does Titanic Survival in Real Time use?
The app employs a variety of machine learning models, including decision trees, random forests, and neural networks, to ensure accurate and robust predictions.
How accurate are the survival predictions?
Accuracy depends on the quality of input data and the specific model used. The tool provides confidence intervals to indicate prediction reliability.
Can I use this tool for educational purposes?
Yes, Titanic Survival in Real Time is an excellent educational resource for teaching machine learning concepts and historical analysis.