block5.fs

// build a training pipeline
let pipeline = 
    EstimatorChain()

        // step 1: map the number column to a key value and store in the label column
        .Append(context.Transforms.Conversion.MapValueToKey("Label", "Number", keyOrdinality = ValueToKeyMappingEstimator.KeyOrdinality.ByValue))

        // step 2: concatenate all feature columns
        .Append(context.Transforms.Concatenate("Features", "PixelValues"))
        
        // step 3: cache data to speed up training                
        .AppendCacheCheckpoint(context)

        // step 4: train the model with SDCA
        .Append(context.MulticlassClassification.Trainers.SdcaMaximumEntropy())

        // step 5: map the label key value back to a number
        .Append(context.Transforms.Conversion.MapKeyToValue("Number", "Label"))

// train the model
let model = trainData |> pipeline.Fit

// the rest of the code goes here....