Added Tutorial Hvass-Labs#8

README.md

@@ -1,8 +1,17 @@
-# TensorFlow-Tutorials
+# TensorFlow Tutorials
 
 [Original repository on GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials)
 
-## Contents
+Original author is [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org)
+
+## Introduction
+
+* These tutorials are intended for beginners in Deep Learning and TensorFlow.
+* Each tutorial covers a single topic.
+* The source-code is well-documented.
+* There is a [YouTube video](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ) for each tutorial.
+
+## Tutorials
 
 1. Simple Linear Model ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/01_Simple_Linear_Model.ipynb))
 
@@ -18,7 +27,98 @@
 
 7. Inception Model ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/07_Inception_Model.ipynb))
 
+8. Transfer Learning ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/08_Transfer_Learning.ipynb))
+
 ## Videos
 
-These tutorials are also available as [YouTube Videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
+These tutorials are also available as [YouTube videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).
+
+## Older Versions
+
+Sometimes the source-code has changed from that shown in the YouTube videos. This may be due to
+bug-fixes, improvements, or because code-sections are moved to separate files for easy re-use.
+
+If you want to see the exact versions of the source-code that were used in the YouTube videos,
+then you can [browse the history](https://github.com/Hvass-Labs/TensorFlow-Tutorials/commits/master)
+of commits to the GitHub repository.
+
+## Installation
+
+Some of the Python Notebooks use source-code located in different files to allow for easy re-use
+across multiple tutorials. It is therefore recommended that you download the whole repository
+from GitHub, instead of just downloading the individual Python Notebooks.
+
+### Git
+
+The easiest way to download and install these tutorials is by using git from the command-line:
+
+    git clone https://github.com/Hvass-Labs/TensorFlow-Tutorials.git
+
+This will create the directory `TensorFlow-Tutorials` and download all the files to it.
+
+This also makes it easy to update the tutorials, simply by executing this command inside that directory:
+
+    git pull
+
+### Zip-File
+
+You can also [download](https://github.com/Hvass-Labs/TensorFlow-Tutorials/archive/master.zip)
+the contents of the GitHub repository as a Zip-file and extract it manually.
+
+## Requirements
+
+There are different ways of installing and running TensorFlow. This section describes how I did it
+for these tutorials. You may want to do it differently and you can search the internet for instructions.
+
+These tutorials were developed on Linux using [Anaconda](https://www.continuum.io/downloads) with Python 3.5 and [PyCharm](https://www.jetbrains.com/pycharm/).
+
+After installing Anaconda, you should create a [conda environment](http://conda.pydata.org/docs/using/envs.html)
+so you do not destroy your main installation in case you make a mistake somewhere:
+
+    conda create --name tf python=3
+
+Now you can switch to the new environment by running the following (on Linux):
+
+    source activate tf
+
+Some of these tutorials use [scikit-learn](http://scikit-learn.org/stable/install.html)
+which can be installed in your new conda environment as follows. This also installs
+NumPy and other dependencies:
+
+    conda install scikit-learn
+
+You may also need to install Jupyter Notebook and matplotlib:
+
+    conda install jupyter matplotlib
+
+Now you have to install TensorFlow. This procedure might change in the future. At the time of this writing,
+the most recent TensorFlow version was 0.10.0. It comes in different builds depending on your needs.
+I need the Python 3.5 build for a Linux PC with only a CPU (no GPU). So I look at the [list of builds](https://www.tensorflow.org/versions/master/get_started/os_setup.html)
+and find the appropriate link which in my case is:
+
+    pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.10.0-cp35-cp35m-linux_x86_64.whl
+
+It is much more complicated to install the GPU-version because you also need various NVIDIA drivers.
+That is not described here.
+
+You should now be able to run the tutorials in the Python Notebooks:
+
+    cd ~/development/TensorFlow-Tutorials/  # Your installation directory.
+    jupyter notebook
+
+This should start a web-browser that shows the list of tutorials. Click on a tutorial to load it.
+
+If you are new to using Python and Linux, etc. then this may be challenging
+to get working and you may need to do internet searches for error-messages, etc.
+It will get easier with practice.
+
+## License (MIT)
+
+These tutorials and source-code are published under the [MIT License](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/LICENSE)
+which allows very broad use for both academic and commercial purposes.
+
+A few of the images used for demonstration purposes may be under copyright. These images are included under the "fair usage" laws.
+
+You are very welcome to modify these tutorials and use them in your own projects.
+Please keep a link to the [original repository](https://github.com/Hvass-Labs/TensorFlow-Tutorials).