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lecture01/lecture_01.py

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+# %% [markdown]
+# # Neuron with 3 inputs
+
+# %%
+inputs = [1, 2, 3]
+weights = [0.2, 0.8, -0.5]
+bias = 2
+
+output = (inputs[0]*weights[0] + inputs[1]*weights[1] + inputs[2]*weights[2] + bias)
+
+print(f"Output: {output}")
+
+# %% [markdown]
+# # Neuron with 4 inputs
+
+# %%
+inputs = [1.0, 2.0, 3.0, 2.5]
+weights = [0.2, 0.8, -0.5, 1.0]
+bias = 2
+
+output = (inputs[0]*weights[0] + inputs[1]*weights[1] + inputs[2]*weights[2] + inputs[3]*weights[3] + bias)
+
+print(output)
+
+# %% [markdown]
+# # Layer of 3 neurons with 4 inputs
+
+# %%
+num_neurons = 3
+num_inputs = 4
+inputs = [1.0, 2.0, 3.0, 2.5]
+weights = [[0.2, 0.8, -0.5, 1.0],
+           [0.5, -0.91, 0.26, -0.5],
+           [-0.26, -0.27, 0.17, 0.87]]
+biases = [2, 3, 0.5]
+
+outputs = []
+for i in range(num_neurons):
+    output = 0
+    for j in range(num_inputs):
+        output += inputs[j]*weights[i][j]
+    output += biases[i]
+    outputs.append(output)
+
+print(outputs)
+
+# %% [markdown]
+# # Layer of 3 neurons with 4 inputs
+
+# %%
+num_neurons = 3
+num_inputs = 4
+inputs = [1.0, 2.0, 3.0, 2.5]
+weights = [[0.2, 0.8, -0.5, 1.0],
+           [0.5, -0.91, 0.26, -0.5],
+           [-0.26, -0.27, 0.17, 0.87]]
+biases = [2, 3, 0.5]
+
+outputs = []
+for neuron_weights, neuron_bias in zip(weights, biases):
+    neuron_output = 0
+    for input, weight in zip(inputs, neuron_weights):
+        neuron_output += input*weight
+    neuron_output += neuron_bias
+    outputs.append(neuron_output)
+
+print(outputs)
+
+# %% [markdown]
+# # Single Neuron using Numpy
+
+# %%
+import numpy as np
+
+inputs = [1.0, 2.0, 3.0, 2.5]
+weights = [0.2, 0.8, -0.5, 1.0]
+bias = 2
+
+output = np.dot(inputs, weights) + bias
+print(output)
+
+