Deep learning is an important subfield of artificial intelligence and we have been working on the modern neural network in our previous tutorials. Today, we are learning the transformer architecture neural network in deep learning. These neural networks have been gaining popularity because they have been used in multiple fields of artificial intelligence and related applications.
In this article, we will discuss the basic introduction of TNNs and will learn about the encoder and decoders in the structure of TNNs. After that, we will see some important features and applications of this neural network. So let’s get started.
What are Transformer Neural Networks
Transformer neural networks (TNNs) were first introduced in 2017. Vaswani et al. h ...
Hello pupils! Welcome to the next section of neural network training. We have been studying modern neural networks in detail, and today we are moving towards the next neural network, which is the Echo State Network (ESN). It is a type of recurrent neural network and is famous because of its simplicity and effectiveness.
In this tutorial, we’ll start learning with the basic introduction of echo state networks. After that, we’ll see the basic concepts that will help us to understand the work of these networks. Just after this, we’ll see the steps involved in setting the ESNs. In the end, we’ll see te fields where ESNs are extensively used. Let’s start with the first topic:
Introduction to Echo State Networks (ESNs)
The echo state networks ( ...
Hello pupils! Welcome to the following lecture on deep learning. As we move forward, we are learning about many of the latest and trendiest tools and techniques, and this course is becoming more interesting. In the previous lecture, you saw some important frameworks in deep learning, and this time, I am here to introduce you to some fantastic algorithms of deep learning that are not only important to understand before going into the practical implementation of the deep learning frameworks but are also interesting to understand the applications of deep learning and related fields. So, get ready to learn the magical algorithms that are making deep learning so effective and cool. Yet before going into details, let me discuss the questions for which we are trying to find answers.
How does dee ...
Hello learners! Welcome to the next episode of Neural Networks. Today, we are learning about a neural network architecture named Vision Transformer, or ViT. It is specially designed for image classification. Neural networks have been the trending topic in deep learning in the last decade and it seems that the studies and application of these networks are going to continue because they are now used even in daily life. The role of neural network architecture in this regard is important.
In this session, we will start our study with the introduction of the Vision Transformer. We’ll see how it works and for this, we’ll see the step-by-step introduction of each point about the vision transformer. After that, we’ll move towards the difference between ViT and CNN and in the end, we’ll discuss th ...
Hello Peeps! Welcome to the next lecture on deep learning, where we are discussing TensorFlow in detail. You have seen why we have chosen TensorFlow for this course, and we have read a lot about the working mechanism, programming languages, and advantages of using TensorFlow instead of other libraries. Instead of using the other options for the same purpose, we have seen several reasons to use TensorFlow. Because of the latest work on the library for more improvement and better results, it's now time to learn the specifics of TensorFlow installation. But before this, you have to check the list of the concepts that will be cleared today:
Is Installation of TensorFlow Difficult?
The simple and to-the-point answer to this question is, the installation is easy and usually does not require ...
Hi readers! I hope you are doing great. We are learning about modern neural networks in deep learning, and in the previous lecture, we saw the capsule neural networks that work with the help of a group of neurons in the form of capsules. Today we will discuss the graph neural network in detail.
Graph neural networks are one of the most basic and trending networks, and a lot of research has been done on them. As a result, there are multiple types of GNNs, and the architecture of these networks is a little bit more complex than the other networks. We will start the discussion with the introduction of GNN.
Introduction to Graph Neural Networks
The work on graphical neural networks started in the 2000s when researchers explored graph-based semi-supervised learning in the neural network. The ...
Hello peeps. Welcome to the next tutorial on deep learning. You have learned about the neural network, and it was an interesting way to compare different types of neural networks. Now, we are talking about deep learning frameworks. In the previous sessions, we introduced you to some important frameworks to let you know about the connection of different entities, but at this level, it is not enough. We are telling you in detail about all types of frameworks that are in style because of their latest features. So before we start, have a look at the list of concepts that will be covered today:
Introduction to the frameworks of deep learning.
Why do we require frameworks in deep learning?
What are some important deep learning frameworks?
What is TensorFlow and for which purpose of using Ten ...
Hey readers! Welcome to the next lecture on neural networks. We are learning about modern neural networks, and today we will see the details of residual networks. Deep learning has provided us with remarkable achievements in recent years, and residual learning is one such output. This neural network has revolutionized the design and training process of the deep neural network for image recognition. This is the reason why we will discuss the introduction and all the content regarding the changes these network has made in the field of computer vision.In this article, we will discuss the basic introduction of residual networks. We will see the concept of residual function and understand the need for this network with the help of its background. After that, we will see the types of skip connec ...
Hey pupil! Welcome to the next lecture on modern neural networks. I hope you are doing great. In the previous lecture, we saw the EffcientNet neural network, which is a convolutional Neural Network (CNN), and its properties. Today, we are talking about another CNN network called the capsule neural network, or CapsNets. These networks were introduced to provide the capsulation in CNNs to provide better functionalities.
In this article, we will start with the introduction of the capsule neural network. After that, we will compare these with the traditional convolutional neural networks and learn some basic applications of these networks. So, let’s start learning.
Introduction to Capsule Neural Networks
Capsule neural networks are a type of artificial neural network that was introduc ...
Hi learners! I hope you are having a good day. In the previous lecture, we saw Kohonen’s neural network, which is a modern type of neural network. We know that modern neural networks are playing a crucial role in maintaining the workings of multiple industries at a higher level. Today we are talking about another neural network named EfficientNet. It is not only a single neural network but a set of different networks that work alike and have the same principles but have their own specialized workings as well.
EfficentNet is providing groundbreaking innovations in the complex fields of deep learning and computer vision. It makes these fields more accessible and, therefore, enhances their range of practical applications. We will start with the introduction, and then we will share some usefu ...
