Introduction to TensorFlow Basics
The following files give a brief 101 intro to TensorFlow. These files were created together for my Introduction to TensorFlow lecture VIDEO | SLIDES
basic_op.py
This file defines some basic operations, setting of constants, variables and operator nodes. It also introduces building a simple model and running a TensorFlow session to run the model.
linear_regression.py
Here we make a simple linear regression using the murder_rates_data.csv dataset to plot training and testing data on a linear regression. We also add TensorBoard summaries to the code which can then be run using tensorboard --logdir="/logs"
logistic_regression.py
Here we expand on the linear regression model and build a logisitic (softmax) regression for the MNIST dataset. The output also includes a nice visual output from two test cases using matplotlib
