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Tag: tf

#007 TF 2.0 An implementation of a Shallow Neural Network in tf.keras – Spirals dataset

20.01.2020

Highlights: In this post we will see how we can classify a spirals dataset with a shallow neural network implemented in TensorFlow 2.0. Tutorial Overview: Imports and Dataset preparation Building a Neural Network Visualization 1. Dataset: import and preparation Let’s start by importing libraries that we will need in our code. Last time we were using a function from sklearn to create a dataset. Now we are going to make our dataset from scratch. First,…
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#006 TF 2.0 An implementation of a Shallow Neural Network in tf.keras – Moons dataset

20.01.2020

In this post we will learn how to make a classification of Moons dataset with a shallow Neural network. The Neural Net we will implemented in TensorFlow 2.0 using Keras API. With the following code we are going to import all libraries that we will need. First, we will generate a random dataset, then we will split it into train and test set. We will also print dimensions of these datasets. With the following code…
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#005 TF 2.0 An implementation of a Shallow Neural Network with tf.keras – Circles dataset

20.01.2020

Highlights: In previous post we have talked about TensorFlow Wrappers and there we concluded that tf.keras is the most convenient way to build neural networks. Now we are going to implement one very simple network using this high-level API. Tutorial Overview: Imports and Dataset preparation Building a Neural Network Visualization 1. Imports and Dataset preparation Let’s start with basic imports. Don’t worry if some things are not familiar with all of these libraries, we will…
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#004 TF 2.0 TensorFlow Wrappers

25.12.2018

Highlights: In this post we are going to talk more about TensorFlow Wrappers. We are going to compare things before and after TensorFlow 2.0. This post will be the introductory one to the series of posts where we are going to build a wide variety of neural networks. To use TensorFlow in our projects, we need to learn how to program using the TensorFlow API. TensorFlow has multiple APIs that can be used to interact with…
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#003 TF 2.0 Eager Execution- A Pythonic way of using TensorFlow

24.12.2018

TensorFlow uses Eager execution, which is a more convenient way to execute the code, and also more “Pythonic”. It is a default choice in the latest version TensorFlow 2.0. In TensorFlow 1.x, we first need to write a Python program that constructs a graph for our computation, the program then invokes Session.run(), which hands the graph off for execution to the C++ runtime. This type of programming is called declarative programming (specification of the computation…
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