Calculate survival probability based on passenger details
Submit models for evaluation and view leaderboard
Measure BERT model performance using WASM and WebGPU
Evaluate model predictions with TruLens
Merge Lora adapters with a base model
Track, rank and evaluate open LLMs and chatbots
View and submit language model evaluations
Measure over-refusal in LLMs using OR-Bench
Rank machines based on LLaMA 7B v2 benchmark results
Display and submit LLM benchmarks
View and submit LLM evaluations
Explain GPU usage for model training
Export Hugging Face models to ONNX
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.