Titanic_prediction

1. Formulated a resilient predictive model using a logestic regression to estimate the probability of survival for Titanic passengers, leveraging sophisticated machine learning methods and feature engineering.
2. Implemented thorough data preprocessing, incorporating techniques such as One-Hot Encoding and Simple Imputation, to elevate the standard and applicability of input data. This process aimed to optimize the subsequent machine learning algorithms for peak performance.
3. Attained a noteworthy accuracy rate of 79.3% through meticulous model training and tuning.