diff --git a/release-packaging/Examples/dataset/MLP-toy-example.scd b/release-packaging/Examples/dataset/MLP-toy-example.scd
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+// basic xor to show non-linearity guestimating of MLP
+// see https://medium.com/@jayeshbahire/the-xor-problem-in-neural-networks-50006411840b
+// and https://youtu.be/188B6k_F9jU
+
+// make 2 datasets as our truth
+(
+Routine{
+	d = Dictionary.new;
+	d.add(\cols -> 2);
+	d.add(\data -> Dictionary.newFrom(["f-f", [0,0], "f-t", [0,1], "t-f", [1,0], "t-t", [1,1]]));
+    ~mlpHelpSource = FluidDataSet.new(s,\mlpHelpSource);
+	s.sync;
+    ~mlpHelpSource.load(d);
+	s.sync;
+	d.add(\cols -> 1);
+	d.add(\data -> Dictionary.newFrom(["f-f", [0], "f-t", [1], "t-f", [1], "t-t", [0]]));
+    ~mlpHelpTarget = FluidDataSet.new(s,\mlpHelpTarget);
+	s.sync;
+    ~mlpHelpTarget.load(d);
+	s.sync;
+}.play;
+)
+
+//check our thruth tables
+~mlpHelpSource.print
+~mlpHelpTarget.print
+
+// make an MLPregressor
+~mlp = FluidMLPRegressor(s,[3],FluidMLPRegressor.sigmoid,1000,0.1,0.1,1,0);//1000 epoch at a time
+//train on it and observe the error
+~mlp.fit(~mlpHelpSource,~mlpHelpTarget,{|x|x.postln;});
+
+//to make a plot of the error let's do a classic 'shades of truth' (a grid of 11 x 11 with each values of truth between 0 and 1
+(
+Routine{
+		d = Dictionary.new;
+
+	d.add(\cols -> 2);
+	d.add(\data -> Dictionary.newFrom(121.collect{|x|[x.asString, [x.div(10)/10,x.mod(10)/10]]}.flatten));
+    ~mlpHelpShades = FluidDataSet.new(s,\mlpHelpShades);
+	s.sync;
+    ~mlpHelpShades.load(d);
+	s.sync;
+}.play;
+)
+
+// check it
+~mlpHelpShades.print
+
+// let's make a destination for our regressions
+~mlpHelpRegressed = FluidDataSet.new(s,\mlpHelpRegressed);
+
+// then predict the full DataSet in our trained network
+~mlp.predict(~mlpHelpShades,~mlpHelpRegressed);
+
+// estimated values
+~mlpHelpRegressed.print;
+
+// lets extract them as an array
+~assignments = Array.new(121); ~mlpHelpRegressed.dump{|x|~assignments = x.at("data").atAll(x.at("data").keys.asArray.sort{|a,b|a.asInteger < b.asInteger}).flatten.postln;};
+
+//and draw them
+(
+w = Window("scatter", Rect(128, 64, 200, 200));
+w.drawFunc = {
+    Pen.use {
+        ~assignments.do{|val,ind|
+			var x = (ind.div(10)*20);
+			var y = (ind.mod(10)*20);
+            var r = Rect(x,y,20,20);
+			Pen.fillColor = Color.grey(val);
+            Pen.fillRect(r);
+        }
+    }
+};
+w.refresh;
+w.front;
+)
+
+
+
+
+
+
+
+
+
+
+
+
+
+~mlpHelpShades.free
+~mlpHelpSource.free
+~mlpHelpTarget.free
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