Book Image

TensorFlow for Neural Network Solutions [Video]

By : Nick McClure
Book Image

TensorFlow for Neural Network Solutions [Video]

By: Nick McClure

Overview of this book

<p>TensorFlow is an open source software library for Machine Intelligence. The independent solutions in this video course will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You’ll work through video on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow.This guide covers important high-level concepts such as neural networks, CNN, RNN, and NLP. Once you are familiar and comfortable with the TensorFlow ecosystem, the last section will show you how to take it to production. Once you are familiar and comfortable with the TensorFlow ecosystem, the last section will show you how to take it to production.</p> <p>All the code and supporting files for this course are available on Github at:<br /><a style="color: #fa8d11;" href="https://github.com/PacktPublishing/TensorFlow-for-Neural-Network-Solutions" target="blank">https://github.com/PacktPublishing/TensorFlow-for-Neural-Network-Solutions</a></p> <h1>Style and Approach</h1> <p>This video course takes a solution-based approach where every topic is explicated with the help of a real-world example.</p>
Table of Contents (6 chapters)
Chapter 1
Neural Networks
Content Locked
Section 3
Working with Gates and Activation Functions
Now that we can link together operational gates, we will want to run the computational graph output through an activation function. Here we introduce common activation functions. - Declare the sigmoid activation model and the ReLU activation model - Loop through training for 750 iterations for both models