Predicts Titanic passenger survival using machine learning (Logistic Regression, Decision Tree, and Random Forest). Analyzes factors like age, gender, and fare to identify key predictors.

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...

The slim volume actually can be read in about 60 minutes (that's what the "1 Hour" in the title refers to) and features short ... "It’s just hugely important, because you’re taking on a ...

TIOBE Index for May 2025: Top 10 Most Popular Programming Languages Your email has been sent Python has pulled far enough ahead of the rest of the other programming languages to have one of the ...

The new categories feature creates virtual buckets for Primary, Transactions, Updates and Promotions, and guesses how your messages should be sorted. If that approach doesn't work for you ...

The importance of immune cell types in the XGBoost model. The influence of immune cell infiltration scores on SHAP values, with a color gradient representing low to high cell infiltration scores.

Data Loading and Preprocessing: Loads the dataset and separates features and target variables. XGBoost Model Training: Trains an XGBoost regression model. Model Evaluation: Evaluates the model using ...