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.
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.
Smoothing normalization is proposed in paper: Attention-Based Models for Speech Recognition. In this tutorial, we will introduce how to implement it in tensorflow.
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.
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.