Updated readme links. Added install instructions

Author: michaelmendoza

README.md

@@ -1,11 +1,11 @@
 # Learning Tensorflow
-
 This tutorial was created for learning tensorflow by example. Currently this repo contains examples for a simple single-layer neural network, a multi-layered perception neural network, and a convolutional neural network. Tensorflow implementations in this repo work with a variety of data sets. Keras implmentations are also included as a comparison for some cases. (Code tested with python 2.7/3.2 using tensorflow 1.3 and keras 2.0)
 
 # Examples
+Examples of tensorflow implementations for Classification, Segmentation, Regression and Modeling Fourier Transform
 
-## Neural Networks
-A variety of neural network implementations for MNIST, and CFAR-10 datasets
+## Classification
+A variety of neural network implementations for MNIST, and CFAR-10 datasets for classification
 
 ### MNIST
 - Basic Neural Network ([tutorial](notebooks/mnist/0_Single_Layer_Network_Tutorial.ipynb), [tensorflow](examples/mnist/basic-net.py)) - A simple (single layer preception) network for classifying MNIST dataset 
@@ -18,3 +18,13 @@ A variety of neural network implementations for MNIST, and CFAR-10 datasets
 - Convolutional Neural Nework ([tensorflow](examples/cifar/conv-net.py), [keras](examples/cifar/keras-conv.py)) - A convolutional network for classifying CIFAR-10 dataset
 - Convolutional Neural Nework ([keras](examples/cifar/keras-nine-layer-conv.py)) - A convolutional network (6-conv, 3 max pool, 2 fully-connected layers) with Dropout for classifying CIFAR-10 dataset 
 - VGG network ([keras](examples/cifar/keras-vgg.py), [paper](https://arxiv.org/pdf/1409.1556v6.pdf)) - A very deep convolutional network for large-scale image recongition
+
+## Segmentation
+Tensorflow implementation for simple color segmentation ([tensorflow](examples/color/segmentation.py))
+
+## Regression
+Neural network implementations for linear ([tensorflow](examples/regression/linear_regression.py)) and non-linear regressions ([tensorflow](examples/regression/non-linear_regression.py))
+
+## Modeling Fourier Transform / FFT
+Neural netowrk implementation for learning a fourier transform ([tensorflow](examples/fft/fft.py))
+

install.md

@@ -0,0 +1,20 @@
+
+
+# Installing with Anaconda and pip
+
+Take the following steps to install Tensorflow and Keras in an Anaconda environment:
+
+1. Download and install Anaconda 
+2. Create a conda environment named 'tf' with the following:
+``` conda create -n tf python=3.5```
+3. Activate the conda environment
+``` activate tf ```
+4. Install Tensorflow inside conda environment (GPU-version):
+``` pip install --upgrade tensorflow-gpu```
+5. Install Keras
+``` pip install --upgrade keras```
+6. Install Matplotlib, Cairos
+``` 
+conda install matplotlib
+conda install pycairo
+```