# 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.

## A Full List of Part-of-Speech of Word in Chinese Jieba Tool – NLP Tutorial

In chinese jieba tool, we have not found a list about chinese part-of-speech used in it. In this tutorial, we will introduce you how to get this list.

## Display WAV FBank Feature with Heatmap – Machine Learning

If you have got the wav fbank feature, you can see it using a heatmap. In this tutorial, we will introduce you how to do.

## Python Extract Audio Fbank Feature for Training – Python Tutorial

If you plan to train deep learning model using wav files, you may have to extract audio features from these files. In this tutorial, we will introduce you how to extract.

## Understand Train Set, Gallery Set and Probe Set in Face Recognition – Deep Learning Tutorial

When you are building face recognition model using deep learning, you have to build a train set, gallery set and probe set to evaluate the performance of your model. In this tutorial, we will introduce these three sets.

## 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.