TensorFlow is an open source platform for machine learning from Google. It can make us to build some AI applications easily. It is a popular deep learning platform in word.

In this page, we write some tutorials and examples on how to use tensorflow, you can build some AI applications by following our tutorials and examples.

When you are using tensorflow to train some deep learning models, you may get some tensors which contains NaN value. How to remove these NaN values in tensor? We will use a simple example to show you how to do.

We have installed a tensorflow version, however, when we use it in python application we get an error: illegal instruction (core dumped). How to fix it? We will introduce you a solution in this tutorial.

Softmax function is differentiable, however, if you get the gradient of it by tf.gradients(), you will get 0. In this tutorial, we will explain the reason for tensorflow beginners.

TensorFlow tf.gradients() function can return the gradient of a tensor. How to understand the result of it? We will use some examples to help tensorflow beginners to understand and use it in this tutorial.

TensorFlow tf.argmax() can allow us to get the index with the largest value across axes of a tensor, which is widely used in classification problems. However, does it support backprop and gradient operation in tensorflow? We will discuss this topic with an example in this tutorial.

When we have installed tensorflow by using whl file, we have got an error: ImportError: DLL load failed with error code -1073741795. Why this error occur and how to fix it. We will discuss these two topics in this tutorial.

TensorFlow can allow us to select elements from a tensor by ids. However, does this function support gradient operation in tensorflow? To address this issue, we will discuss this topic in this tutorial.

When we are installing tensorflow with whl file, we have encountered an error: Cannot uninstall ‘wrapt’. It is a distutils installed project. In this tutorial, we will introduce how to fix it for tensorflow beginners.

In this tutorial, we will discuss how to compute the gradient of svd after replacing tf.svd() with numpy.linalg.svd() with some examples, you can learn and how to do from this tutorial.

This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Cookie settingsACCEPT

Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website.

Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.