An Introduction to MagFace for Beginners – Deep Learning Tutorial
In this tutorial, we will introduce MagFace to beginners, it is a good way to measure the quality of the given face.
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 Bahdanau Attention for Beginners – Deep Learning Tutorial
In this tutorial, we will introduce what is bahdanau attention mechanism and how to implement it.
Regularizing LSTM at Each Timestep with Zoneout – Deep Learning Tutorial
Zoneout is proposed in paper: Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations. It is also used in Tacotron 2. In this tutorial, we will introduce what it is and how to implement it using tensorflow.
Understand Smoothing Normalization in Speech Recognition – Deep Learning Tutorial
Smoothing normalization is proposed in paper: Attention-Based Models for Speech Recognition. In this tutorial, we will introduce how to implement it in tensorflow.
Understand Dropout – Place it Before or After Activation Function in Dense Layer?
In deep learning, we usually place a dropout layer after a dense layer. However, here is a problem? Dropout layer is placed before or after activation function.
Post-Norm and Pre-Norm Residual Units Explained – Deep Learning Tutorial
In this tutorial, we will introduce post-norm and pre-norm residual units, they are often used to improve transformer in deep learning.
Dropout vs Batch Normalization – Which is Better for Multilayered Neural Network
Dropout and batch normalization are two well-recognized approaches to tackle overfitting in multilayered neural networks, which one is better? In this tutorial, we will discuss this topic.
An Introduction to GE2E Loss for Beginners – Deep Learning Tutorial
GE2E loss is proposed in paper << GENERALIZED END-TO-END LOSS FOR SPEAKER VERIFICATION>>. In this tutorial, we will introduce it for some beginners.
Compute KL (Kullback–Leibler) Divergence Between Two Multivariate Gaussian Distributions – Machine Learning Tutorial
In this tutorial, we will introduce how to compute KL (Kullback–Leibler) divergence between two multivariate gaussian distributions.
An Introduction to Accuracy, Precision, Recall & F1-Score in Machine Learning – Machine Learning Tutorial
Accuracy, Precision, Recall & F1-Score are widely used in machine learning. In this tutorial, we will discuss how to compute them.
