For this set of lessons, I am assuming that you already have some familiarity with artificial neural networks, matrices, vectors and feel comfortable with Python, and numpy. I am also assuming that you have installed Tensorflow. If not then please head over to the official tensorflow installation guide and follow the instructions for your operating system.
This set of lessons can best be thought of as supplemental material to the official documentation. The aim is to explain different components of tensorflow in a more gentle conversational way.
There is no particular ordering to the lessons. The numbered lessons are simply a suggested order for people that are very new to tensorflow since they cover the absolute basics. But any lessons without numbering have no order at all. Just chose whatever component of tensorflow you are most interested in learning about.
This is a work in progress, so please come and visit occasionally, as I will constantly be adding more lessons here.
Most of the examples in this series of lessons will build off of the following template of code. The meaning of these sections in the code will be explained in the following lesson.
from __future__ import print_function, division
import tensorflow as tf
import numpy as np
# ------------------------------------------------
# Build a graph
# ------------------------------------------------
graph = tf.Graph()
with graph.as_default():
pass # REPLACE WITH YOUR CODE TO BUILD A GRAPH
# ------------------------------------------------
# Create a session and run the graph
# ------------------------------------------------
with tf.Session(graph=graph) as session:
pass # REPLACE WITH YOUR CODE TO RUN A SESSION