🛠️ adding submodules to PINNs and renaming things

PINN.yml

@@ -0,0 +1,15 @@
+name: CNN
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python
+  - keras
+  - tensorflow=2.3
+  - pydot
+  - graphviz
+  - ipdb
+  - matplotlib=3.0
+  - basemap-data-hires
+  - geopy
+  - notebook

Physics_Informed_NNs.ipynb

@@ -16,14 +16,56 @@
    "id": "1cf2aeb8",
    "metadata": {},
    "source": [
-    "# Overview"
+    "# Overview\n",
+    "\n",
+    "This notebook is based on two papers: *[Physics-Informed Neural Networks:  A Deep LearningFramework for Solving Forward and Inverse ProblemsInvolving Nonlinear Partial Differential Equations](https://www.sciencedirect.com/science/article/pii/S0021999118307125)* and *[Hidden Physics Models:  Machine Learning of NonlinearPartial Differential Equations](https://www.sciencedirect.com/science/article/pii/S0021999117309014)* with the help of  Fergus Shone and Michael Macraild."
    ]
   },
   {
    "cell_type": "markdown",
    "id": "10361a00",
    "metadata": {},
-   "source": []
+   "source": [
+    "<div style=\"background-color: #ccffcc; padding: 10px;\">\n",
+    "\n",
+    "<h1>Physics Informed Neural Networks</h1>\n",
+    "\n",
+    "\n",
+    " \n",
+    "## The very basics\n",
+    "\n",
+    "If you know nothing about neural networks there is a [toy neural network python code example](https://github.com/cemac/LIFD_ENV_ML_NOTEBOOKS/tree/main/ToyNeuralNetwork) included in the [LIFD ENV ML Notebooks Repository]( https://github.com/cemac/LIFD_ENV_ML_NOTEBOOKS). Creating a 2 layer neural network to illustrate the fundamentals of how Neural Networks work and the equivlent code using the python machine learning library [tensorflow](https://keras.io/). \n",
+    "\n",
+    "    \n",
+    "## Recommended reading \n",
+    "    \n",
+    "The in-depth theory behind neural networks will not be covered here as this tutorial is focusing on application of machine learning methods. If you wish to learn more here are some great starting points.     \n",
+    "\n",
+    "</div>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0c2d1f44",
+   "metadata": {},
+   "source": [
+    "<hr>\n",
+    "\n",
+    "\n",
+    "<div style=\"background-color: #e6ccff; padding: 10px;\">\n",
+    "    \n",
+    "<h1> Machine Learning Theory </h1>\n",
+    "<a href=\"\">\n",
+    "<img src=\"\">\n",
+    "</a>\n",
+    "\n",
+    "    \n",
+    "## Neural Networks\n",
+    "\n",
+    "  \n",
+    "    \n",
+    "</div>    "
+   ]
   },
   {
    "cell_type": "markdown",