Add Python project examples

+ Neural network CLI
+ Hidden Markov Model CLI
+ K-Means clustering CLI
+ Linear regression CLI
+ Screenshots, updated README instructions

python/neural-network/input-test.json

@@ -0,0 +1,44 @@
+{
+  "inputs": 6,
+  "perceptrons": 8,
+  "outputs": 10,
+  "hidden_layers": 3,
+  "learn_rate": 0.25,
+  "fire_threshold": 0.25,
+  "error_threshold": 0.5,
+  "cycles": 10,
+  "spacing": 2.0,
+  "horizontal": true,
+  "input_sequence": [
+    [0, 1, 0, 1, 1, 1],
+    [0, 0, 0, 0, 1, 1],
+    [0, 1, 0, 1, 1, 1],
+    [0, 1, 0, 1, 1, 1],
+    [0, 1, 0, 1, 1, 1],
+    [1, 1, 1, 1, 1, 1],
+    [1, 1, 1, 1, 1, 1],
+    [1, 1, 1, 1, 1, 1],
+    [1, 1, 1, 1, 1, 1],
+    [0, 1, 0, 1, 1, 1],
+    [0, 1, 0, 1, 1, 1],
+    [0, 1, 0, 1, 1, 1],
+    [0, 1, 0, 1, 1, 1],
+    [0, 1, 0, 1, 1, 1]
+  ],
+  "label_sequence": [
+    [1, 0, 0, 0, 0, 0, 0, 0],
+    [0, 1, 0, 0, 0, 0, 0, 0],
+    [0, 0, 1, 0, 0, 0, 0, 0],
+    [0, 0, 0, 1, 0, 0, 0, 0],
+    [0, 0, 0, 0, 1, 0, 0, 0],
+    [0, 0, 0, 0, 0, 1, 0, 0],
+    [0, 0, 0, 0, 0, 0, 1, 0],
+    [0, 0, 0, 0, 0, 0, 0, 1],
+    [0, 0, 0, 0, 0, 0, 0, 1],
+    [0, 0, 0, 0, 0, 0, 0, 1],
+    [0, 0, 0, 0, 0, 0, 0, 1],
+    [0, 0, 0, 0, 0, 0, 0, 1],
+    [0, 0, 0, 0, 0, 0, 0, 1],
+    [0, 0, 0, 0, 0, 0, 0, 1]
+  ]
+}