diff --git a/Color_Perceptron/Color_Perceptron.ino b/Color_Perceptron/Color_Perceptron.ino
deleted file mode 100644
index eae5089..0000000
--- a/Color_Perceptron/Color_Perceptron.ino
+++ /dev/null
@@ -1,134 +0,0 @@
-/*
-
-Perceptron example
-
-Hardware: Arduino Nano BLE Sense
-
-Usage: Follow the prompts in the Serial Monitor and show two objects of different colors to the color sensor onboard the Arduino.
-The sketch will train a perceptron using these examples, and then classify objects you show it in the future.
-
-The color sensor works better in a well lit area
-
-*/
-
-#include <Arduino_APDS9960.h>
-#include <Arduino_Perceptron.h>
-
-const int   NUM_INPUTS          = 3;     // Red, green and blue
-const int   CLASSES             = 2;     // The perceptron only has 2 possible classes
-const int   EXAMPLES            = 30;    // Number of samples for each object
-const int   NUM_EPOCHS          = 100;   // Maximum training iterations
-const float LEARNING_RATE       = 0.001; // Perceptron learning rate
-const int   THRESHOLD           = 5;     // Color sensor light threshold
-
-float       input[NUM_INPUTS];
-float       weights[NUM_INPUTS+1];       // Weights for each color input + the bias
-String      label[CLASSES] = {"object A", "object B"};
-
-Perceptron  perceptron(NUM_INPUTS, LEARNING_RATE);
-
-void setup() {
-  Serial.begin(9600);
-  while (!Serial);
-
-  if (!APDS.begin()) {
-    Serial.println("Failed to initialize APDS color sensor!");
-    while (1);
-  }
-
-  Serial.println("Arduino perceptron");
-
-  // Get example color data
-  // ----------------------
-  for (int thisClass = 0; thisClass <= 1; thisClass++) {
-
-    Serial.print("Show me ");
-    Serial.println(label[thisClass]);
-
-    // Wait for the object to move away again
-    while (!APDS.proximityAvailable() || APDS.readProximity() == 0) {}
-
-    // Get n color samples from the object
-    for (int n = 0; n < EXAMPLES; n++) {
-      readColor(input); // red, green and blue
-      perceptron.addExample(input, thisClass); // Add to training set
-    }
-  }
-
-  // Train the perceptron
-  // --------------------
-  Serial.println("\nTraining perceptron");
-  int epoch = 0;
-  float accuracy = 0;
-
-  Serial.print("Start weights:");
-  printWeights();
-
-  for (int epoch = 0; epoch < NUM_EPOCHS; epoch++) {
-    accuracy = perceptron.train();
-    Serial.print("Accuracy: ");
-    Serial.println(accuracy);
-  }
-
-  Serial.print("End weights:");
-  printWeights();
-
-  Serial.println("Training complete\n");
-}
-
-
-// Classify objects shown
-// ----------------------
-void loop() {
-
-  int output;
-
-  // Wait for the object to move away again
-  while (!APDS.proximityAvailable() || APDS.readProximity() == 0) {}
-
-  Serial.println("Let me guess your object");
-
-  readColor(input);
-
-  output = perceptron.classify(input);
-
-  Serial.print("You showed me ");
-  Serial.println(label[output]);
-}
-
-
-void readColor(float color[]) {
-  int red, green, blue;
-
-  // Loop until we have a color sample bright enough
-  while (red+green+blue < THRESHOLD) {
-    // Sample if color sensor is available and the object is close
-    if (APDS.colorAvailable() && APDS.proximityAvailable() && APDS.readProximity() == 0) {
-      APDS.readColor(red, green, blue);
-    }
-  }
-
-  // Put color sample data in input array
-  color[0] = (float)red;
-  color[1] = (float)green;
-  color[2] = (float)blue;
-
-  // Print the red, green and blue values
-  printArray(color,NUM_INPUTS);
-}
-
-
-void printWeights() {
-  perceptron.getWeights(weights,NUM_INPUTS+1); // input weights plus the bias
-  printArray(weights,NUM_INPUTS+1);
-}
-
-
-void printArray(float myArray[], int length) {
-  Serial.print(myArray[0]);
-  for (int n = 1; n < length; n++) {
-    Serial.print(",");
-    Serial.print(myArray[n]);
-  }
-  Serial.println();
-}