Adding the initial neuralnet files

neuralnet/neuralnetwork.py

@@ -0,0 +1,26 @@
+import numpy as np
+from tensorflow.keras.models import Sequential
+from tensorflow.keras.layers import Dense
+
+# create NeuralNetwork class
+class NeuralNetwork:
+    def __init__(self, inputs_len: int):
+        # Setup checkpoint
+        self.checkpoint_path = "./training/cp.ckpt"
+        self.cp_callback = tf.keras.callbacks.ModelCheckpoint(filepath=checkpoint_path, save_weights_only=True, verbose=1)
+
+        # Setup model
+        self.model = Sequential()
+        self.model.add(Dense(12, input_shape=(inputs_len,), activation='relu'))
+        self.model.add(Dense(8, activation='relu'))
+        self.model.add(Dense(1, activation='sigmoid'))
+        self.model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
+
+        if os.path.isfile(self.checkpoint_path):
+            self.model.load_weights(self.checkpoint_path)
+
+    def train(inputs :list, outputs :list):
+        self.model.fit(inputs, outputs, epochs=150, batch_size=10, callbacks=[self.cp_callback])
+
+    def predict(self, new_input):
+        return self.model.predict(new_input)