# Machine Learning Tutorials and Examples for Beginners

Machine learning is a data analytics technique that teaches computers to do what comes naturally to humans and animals: learn from experience.

In this page, we write some tutorials and examples on machine learning algorithms and applications. You can learn how to use machine learning in life by following our tutorials.

## An Introduction to Audio V3 Format Extension – Deep Learning Tutorial

In this tutorial, we will introduce audio V3 format for users who want to process them.

## Implement Focal Loss for Multi Label Classification in TensorFlow

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.

## Understand Exponential Function in Machine Learning – Machine Learning Tutorial

In this tutorial, we will introduce some important features on exponential functionwhen using it.

## Batch Normalization Vs Layer Normalization: The Difference Explained

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 Explained for Beginners – Deep Learning Tutorial

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.

## Understand Gated Self-Attention for Beginners – Deep Learning Tutorial

Gated Self-Attention is an improvement of self-attention mechanism. In this tutorial, we will discuss it for deep learning beginners.

## Understand Maxout Activation Function in Deep Learning – Deep Learning Tutorial

Maxout activation functionin is proposed in paper <>. In this tutorial, we will introduce it with some examples.

## Understand Multi-Head Attention in Deep Learning – Deep Learning Tutorial

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.

## Understand Jensen’s Inequality and Attention Mechanism in Deep Learning – Deep Learning Tutorial

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.

## Feature Fusion: Pointwise Addition Or Concatenate Vectors? – Deep Learning Tutorial

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.