/**
 * The {@link ML} module facilitates creation of Automated Machine Learning models to embed into {@link Template}s.
 *
 * @module ML
 *
 * @example
 * ```typescript
 *   // use a DictType stream
 *   const training_stream = Stream(
 *       "My Training Stream",
 *       DictType(
 *           StringType,
 *           StructType({
 *               qty: FloatType,
 *               price: FloatType,
 *           })
 *       )
 *   );
 *
 *   const prediction_stream = Stream(
 *       "My Prediction Stream",
 *       DictType(
 *           StringType,
 *           StructType({
 *               price: FloatType,
 *           })
 *       )
 *   );
 *
 *   // create a GP to predict demand based on price
 *   const demand = new MLModelBuilder("Demand")
 *       .feature("price", FloatType)
 *       .output(FloatType)
 *       .trainFromStream({
 *           output_name: "qty",
 *           input: training_stream,
 *       });
 *
 *   // directly predict the model outputs from features
 *   const ml_prediction = new MLPredictionBuilder("ML Prediction")
 *     .model(demand)
 *     .predict(prediction_stream);
 *
 *   // or alternatively use the model to predict in a process
 *   // create the sales process and add the ml function
 *   // which is evaluated in each sale
 *   const sales = new ProcessBuilder("sales")
 *       // the ml function can be added
 *       .ml(demand)
 *       // the sale needs a price
 *       .value("price", FloatType)
 *       // the ml can be evaluated
 *       .let(
 *           "qty",
 *           (props, _resources, mls) => mls.demand(Struct({ price: props.price }))
 *       )
 *       .mapFromValue({ date: new Date(0), price: 10 });
 *
 * ```
 */
export * from './MLModelBuilder';
export * from './MLPredictionBuilder';