Focal loss is a good method to improve the model performance for imbalance multi label classification. In this tutorial, we will implement it using tensorflow.
In this tutorial, we will introduce some important features on exponential functionwhen using it.
Both Batch Normalization and Layer Normalization can normalize the input \(x\). What is the difference between them. In this tutorial, we will introduce it.
Layer Normalization is proposed in paper “Layer Normalization” in 2016. In this tutorial, we will introduce what is layer normalization and how to use it.
Gated Self-Attention is an improvement of self-attention mechanism. In this tutorial, we will discuss it for deep learning beginners.
Maxout activation functionin is proposed in paper <>. In this tutorial, we will introduce it with some examples.
Multi-Head Attention is very popular in nlp. However, there also exists some problems in it. In this tutorial, we will discuss how to implement it in tensorflow.
Attention mechanism is an important method to improve the performance of deep learning model. There are two forms of attention, which one we should use? In this tutorial, we will find some tips.
In deep learning, we often use a vector to express a target feature, however, how to fuse them if we have got some features? In this tutorial, we will discuss this topic.
Out-Of-Vocabulary (OOV) words is an important problem in NLP, we will introduce how to process words that are out of vocabulary in this tutorial.