Zipline Python: Backtesting Pipelines, Data, and Risk Checks
Evaluate Zipline Python backtests with an isolated environment, clean historical data, explicit signals, transaction costs, and careful performance metrics.
Machine Learning
Learn machine learning in Python with beginner tutorials, libraries, models, data preparation, examples, evaluation, and practical workflows.
CatBoostRegressor Target Transform: Log, Scale, and Inverse
Apply target transforms with CatBoostRegressor safely, compare log and scaling choices, avoid leakage, and convert predictions back to the original units.
PyCaret create_api(): Create and Test a Machine Learning API
Use PyCaret create_api workflows carefully by checking module versions, saved models, request schemas, authentication, deployment settings, and API tests.
Autocorrelation in Python: Formula, Lags, and Reliable Analysis
Compute autocorrelation in Python with centered series, lag conventions, missing values, normalization, confidence limits, and time-series checks.
