# codez 2.0.0

* Migrated the neural backend from TensorFlow/Keras to torch.
* Added `fit_codez()` and `codez_control()` as the v2 workflow API.
* Added tidy forecast extraction via `codez_forecast_tidy()` and S3 helpers for
  `predict()`, `summary()`, `autoplot()`, `plot()`, and `as.data.frame()`.
* Added rolling naive and average baseline backtests for numeric data.
* Added training controls for `batch_size`, `validation_split`, and `n_sim`.
* Fixed mixed-type detection, forward-net L2 sampling, finite-solution routing,
  duplicate `plotter()` definition, and average benchmark calculation.
* Replaced non-core convenience dependencies with local support functions for
  mapping, dummy encoding, interpolation, smoothing, metrics, distances,
  moments, entropy, array binding/splitting, timing, and plotting.

# codez 1.0.0

* Added a `NEWS.md` file to track changes to the package.
