From 91e4e2759e952f589aec8650e6e1dea0e5d5f919 Mon Sep 17 00:00:00 2001
From: Brandon Rodriguez <brodriguez8774@gmail.com>
Date: Fri, 9 Oct 2020 07:43:56 -0400
Subject: [PATCH] Update readme

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 readme.md | 26 ++++++++++++++++++++------
 1 file changed, 20 insertions(+), 6 deletions(-)

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+# Python - Intro to Tensorflow
 
-# CS5300 a2
 
+## Description
+Neural Network Tensorflow examination. Used the [CIFAR-10](http://www.cs.toronto.edu/~kriz/cifar.html) image dataset to train a network. The end goal is to have a
+network that can look at a given image and accurately give it a label (ex: "bird", "dog", "train", "truck", etc).
 
-## Author
-Brandon Rodriguez
+Project actually used two different neural network types.
 
+The first one was a "deep layer" network, which is essentially what the previous assignments were. This network examined
+pixels one by one, and made decisions from that.
+
+The second network was a "convolutional" network, which is designed specifically for examining groups of pixels
+together, as a single unit. Both grouping and meaning of group is determined by network, in the learning stages.
+
+Both networks had high accuracy, but the Convolutional network was noticably higher across the board.
 
-## Description
 
-Neural Network Tensorflow examination.
+## TensorFlow
+TensorFlow is a Neural Net library for Python. It essentially acts as an easy interface directly to C++ Neural Network
+code. For the most part, this allows for the ease of syntax that Python brings, but the speed and efficiency of C++ code.
 
+Due to the complexity (both logically and computationally) of Neural Nets, it's rare to implement one's own Neural Net
+logic over using a prebuilt library.
+
+
+## References
 Tutorials from:
 * https://www.tensorflow.org/versions/r1.0/get_started/mnist/beginners
 * https://www.tensorflow.org/versions/r1.0/get_started/mnist/pros
 * https://www.tensorflow.org/tutorials/deep_cnn
-
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