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.
TensorFlow tf.concat() function is widely used in deep learning, especially when you are creating bilstm with tensorflow. In this tutorial, we will write some examples to help you understand it.
Both numpy.split() and tf.split() can split an array or a tensor into some sub arrays and tensors. However, there exsits some differences between them. In this tutorial, we will compare with them to help you understand.
We often use tensorflow tf.concat() function to concatenate tensors, however, we may encounter TypeError: Tensors in list passed to ‘values’ of ‘ConcatV2’ Op have types [int32, float32] that don’t all match. How to fix this error? Why does it occur? In this tutorial, we will discuss it and tell you how to fix it.
When you are using tensorflow to training your model, you may find an error: the value of loss function is getting bigger and bigger when training. How to solve this problem? In this tutorial, we will discuss two ways to fix this error.
TensorFlow tf.nn.softmax_cross_entropy_with_logits_v2() is one of functions which tensorflow use to compute cross entropy, which is very similar to tf.nn.softmax_cross_entropy_with_logits(). In this tutorial, we will introduce how to use this function for tensorflow beginners.
When you are running tensorflow application, you may find this warning: FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated; in a future version of numpy. How to fix this warning? In this tutorial, we will introduce you some steps, you can fix this warning by following our tutorial.
TensorFlow provides some functions to compute cross entropy loss, however, these functions will compute sigmoid or softmax value for logists. How to compute cross entropy loss without computing softmax or sigmoid value of logits? In this tutorial, we will tell you how to do.
TensorFlow tf.nn.sigmoid_cross_entropy_with_logits() is one of functions which calculate cross entropy. In this tutorial, we will introduce some tips on using this function. As a tensorflow beginner, you should notice these tips.
Conda can allow us to install specific tensorflow version, which is very useful when you are learning tensorflow. In this tutorial, we will introduce you how to install by using conda.
TensorFlow tf.argmax() function is often used in classification problem. In order to get the predictions, we often use this function. In this tutorial, we will introduce how to use this function correctly for tensorflow beginners.