diff --git a/notebooks/wut-predict.ipynb b/notebooks/wut-predict.ipynb
index de94d95..28f9e63 100644
--- a/notebooks/wut-predict.ipynb
+++ b/notebooks/wut-predict.ipynb
@@ -74,29 +74,12 @@
     "from sklearn.decomposition import PCA\n",
     "\n",
     "# Seaborn pip dependency\n",
-    "import seaborn as sns"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Interact\n",
-    "# https://ipywidgets.readthedocs.io/en/stable/examples/Using%20Interact.html\n",
+    "import seaborn as sns\n",
+    "\n",
     "from __future__ import print_function\n",
     "from ipywidgets import interact, interactive, fixed, interact_manual\n",
-    "import ipywidgets as widgets"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Display Images\n",
+    "import ipywidgets as widgets\n",
+    "\n",
     "from IPython.display import display, Image"
    ]
   },
@@ -106,7 +89,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ENCODING='FSK9k6'"
+    "#ENCODING='APT'\n",
+    "#ENCODING='CW'\n",
+    "#ENCODING='FM'\n",
+    "#ENCODING='FSK9k6'\n",
+    "ENCODING='GMSK2k4'\n",
+    "#ENCODING='GMSK4k8'\n",
+    "#ENCODING='USB'"
    ]
   },
   {
@@ -208,7 +197,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "print(num_test)"
+    "print(\"Number of observations to test:\", num_test)"
    ]
   },
   {
@@ -217,7 +206,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# This function will plot images in the form of a grid with 1 row and 3 columns where images are placed in each column.\n",
     "def plotImages(images_arr):\n",
     "    fig, axes = plt.subplots(1, 3, figsize=(20,20))\n",
     "    axes = axes.flatten()\n",
@@ -301,6 +289,13 @@
     "  rating = 'good'\n",
     "print('Observation: %s' % (rating))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/notebooks/wut-train.ipynb b/notebooks/wut-train.ipynb
index be2d819..23495b4 100644
--- a/notebooks/wut-train.ipynb
+++ b/notebooks/wut-train.ipynb
@@ -69,18 +69,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Visualization\n",
     "%matplotlib inline\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "from sklearn.decomposition import PCA\n",
-    "# Seaborn pip dependency\n",
     "import seaborn as sns\n",
-    "# Interact\n",
-    "# https://ipywidgets.readthedocs.io/en/stable/examples/Using%20Interact.html\n",
     "from ipywidgets import interact, interactive, fixed, interact_manual\n",
     "import ipywidgets as widgets\n",
-    "# Display Images\n",
     "from IPython.display import display, Image\n",
     "from IPython.display import SVG"
    ]
@@ -91,13 +86,35 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ENCODING='FSK9k6'\n",
-    "#batch_size = 64\n",
+    "#ENCODING='APT'\n",
+    "#ENCODING='BPSK1k2' # Fail\n",
+    "#ENCODING='FSK9k6'\n",
+    "#ENCODING='FM'\n",
+    "ENCODING='GMSK2k4'\n",
+    "#ENCODING='GMSK4k8'\n",
+    "#ENCODING='USB'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#batch_size = 8\n",
+    "#atch_size = 16\n",
+    "#atch_size = 32\n",
+    "batch_size = 64\n",
+    "#batch_size = 128\n",
+    "#batch_size = 256\n",
     "#epochs = 4\n",
-    "batch_size = 128\n",
-    "epochs = 4\n",
+    "epochs = 8\n",
+    "#IMG_WIDTH = 208\n",
+    "#IMG_HEIGHT = 402\n",
     "IMG_WIDTH = 416\n",
-    "IMG_HEIGHT = 803"
+    "IMG_HEIGHT = 803\n",
+    "#IMG_WIDTH = 823\n",
+    "#IMG_HEIGHT = 1603"
    ]
   },
   {
@@ -133,9 +150,9 @@
     "print('Validation bad images:  ', num_val_bad)\n",
     "print('Validation images:      ', total_val)\n",
     "print('')\n",
-    "print('Reduce training and validation set')\n",
-    "total_train = 5000\n",
-    "total_val = 5000\n",
+    "#print('Reduce training and validation set')\n",
+    "#total_train = 1000\n",
+    "#total_val = 1000\n",
     "print('Training reduced to:    ', total_train)\n",
     "print('Validation reduced to:  ', total_val)"
    ]
@@ -390,7 +407,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "loss = history.history['loss']\n",
@@ -398,8 +417,10 @@
     "\n",
     "epochs_range = range(epochs)\n",
     "\n",
+    "save_plot_dir = os.path.join('/srv/satnogs/data/models/', ENCODING)\n",
+    "os.makedirs(save_plot_dir, exist_ok=True)\n",
     "plot_file=(\"wut-plot-\" + ENCODING + \".png\")\n",
-    "save_path_plot = os.path.join('/srv/satnogs/data/models/', ENCODING, plot_file)\n",
+    "save_path_plot = os.path.join(save_plot_dir, plot_file)\n",
     "print(save_path_plot)\n",
     "\n",
     "plt.figure(figsize=(8, 8))\n",
@@ -491,6 +512,13 @@
    "source": [
     "#SVG(model_to_dot(model).create(prog='dot', format='svg'))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/notebooks/wut.ipynb b/notebooks/wut.ipynb
index 29d7efa..ca2a489 100644
--- a/notebooks/wut.ipynb
+++ b/notebooks/wut.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,24 +47,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Start\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(\"Start\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -73,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -82,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -91,7 +83,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -116,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,7 +121,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -139,7 +131,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -152,7 +144,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -162,24 +154,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Python import done\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(\"Python import done\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -190,7 +174,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -200,7 +184,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -210,7 +194,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -220,7 +204,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -230,7 +214,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -239,7 +223,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -249,20 +233,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "total training good images: 16739\n",
-      "total training bad images: 3961\n",
-      "--\n",
-      "Total training images: 20700\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print('total training good images:', num_train_good)\n",
     "print('total training bad images:', num_train_bad)\n",
@@ -272,20 +245,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "total validation good images: 16716\n",
-      "total validation bad images: 3934\n",
-      "--\n",
-      "Total validation images: 20650\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print('total validation good images:', num_val_good)\n",
     "print('total validation bad images:', num_val_bad)\n",