Updated notice for TensorFlow and future math book.

Author: jeffheaton

.gitignore

@@ -94,3 +94,4 @@ install_manifest.txt
 
 # Other files
 *.gz
+.ipynb_checkpoints

help/README.md

@@ -0,0 +1,29 @@
+AIFH: Introduction to the Math of Neural Networks
+=================================================
+
+**Please note: This material is for an upcoming book.**
+
+This book has the following chapters:
+
+* Chapter 1. Activation
+* Chapter 2. Error Calculation
+* Chapter 3. Differentiation
+* Chapter 4. Numeric Differentiation
+* Chapter 5. Symbolic Differentation
+* Chapter 6. Backpropagation
+* Chapter 7. Enhancements to Backpropagation
+* Chapter 8. Linear Algebra
+* Chapter 9. Integration
+* Chapter 10. Probability
+* Chapter 11. Statistics
+* Chapter 12. Pseudo Random Number Generation
+* Chapter 13. Self-Organizing Maps
+* Chapter 14. Preprocessing
+
+The following language ports have been completed for this book.  See the individual 
+README files inside of each chapter for language specific instructions. If you find a bug,
+or improve an example, please consider pushing a change via GitHub.
+	
+## Getting Help
+
+* [Q&A Forum on Google Groups](https://groups.google.com/forum/#!forum/jeffheatons-ai-group)

math/README.md

@@ -0,0 +1,55 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "[Artificial Intelligence for Humans](http://www.heatonresearch.com/aifh/)\n",
+    "\n",
+    "**Introduction to the Math of Neural Networks**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "\n",
+    "**Equation 1.1: The Summation Operator**\n",
+    "$$ s = \\sum_{i=1}^{10} 2i $$\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python [conda env:tensorflow]",
+   "language": "python",
+   "name": "conda-env-tensorflow-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

math/Untitled.ipynb

@@ -1,10 +1,6 @@
 AIFH Vol3  - C# Code Examples
 ====
 
-**Note: I am in the process of refactoring the conv-nets in the C# versions to use [CNTK](https://github.com/Microsoft/CNTK), 
-this is to provide greater performance. Sorry for any inconvenience, I hope to have the 
-new version complete by the end of June 2016.**
-
 This folder contains the C# examples for AIFH Volume 2.  This software was developed using Visual Studio 2012.
 
 Two 3rd party DLLs are also used. They are both included in the project via NUGET.

vol3/vol3-csharp-examples/README.md

@@ -17,6 +17,9 @@ Anaconda is what I used while developing these examples.
 
 ##Required Libraries
 
+** Please note (17 Jan 2017): I am in the process of changing the Python examples to use Google TensorFlow, instead of Lasange. **
+** I hope to complete this around the time of TensorFlow 1.0's release. **
+
 The Python programming language has some of the most advanced deep learning neural network
 frameworks available of any language.  These libraries are designed for maximum 
 efficiency and computational power.  Most of these frameworks can also use a GPU to