Deep learning has applications in multiple industries, and this has made it an important and attractive topic for researchers. The interest of researchers has resulted in multiple types of neural networks we have been discussing in this series so far. Today, we are talking about generative advertising neural networks (GAN). This algorithm performs the unsupervised learning task and is used in different fields of life such as education, medicine, computer vision, natural language processing (NLP), etc.
In this article, we will discuss the basic introduction of GAN and will see the working mechanism of this neural network, After that, we will see some important applications of GANs and discuss some real-life examples to understand the concept. So let’s move towards the introduction of GANs ...
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 ...
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 ...
Hi there! I hope you are having a great day. The success of the field of deep learning is due to its complex and advanced neural networks. These networks can be broadly divided into traditional and modern neural networks. We have seen the details of traditional neural networks, and in the previous session, the basic introduction of modern neural networks and the details of their features were discussed. Today, we will talk about one of the most famous modern neural networks, the Kohonen Self-Organized Neural Network.
Modern neural networks are more organized and developed than traditional neural networks, but that does not make traditional neural networks less efficient than modern ones. All the networks are introduced for specific tasks, and this is one of the main reasons behind t ...
Hey pupils! Welcome to the next session on modern neural networks. We are studying the basic neural networks that are revolutionizing different domains of life. In the previous session, we read the Deep Q Networks (DQN) Reinforcement Learning (add link). There, the basic concepts and applications were discussed in detail. Today, we will move towards another neural network, which is an improvement in the deep Q network and is named the double deep Q network.
In this article, we will point towards the basic workings of DQN as well so I recommend you read the deep Q networks if you don’t have a grip on this topic. We will introduce the DDQN in detail and will know the basic needs for improvement in the deep Q network. After that, we’ll discuss the history of these networks and learn ab ...
Hey readers! Welcome to the next episode of training on neural networks. We have been studying multiple modern neural networks and today we’ll talk about autoencoders. Along with data compression and feature extraction, autoencoders are extensively used in different fields. Today, we’ll understand the multiple features of these neural networks to understand their importance.In this tutorial, we’ll start learning with the introduction of autoencoders. After that, we’ll go through the basic concept to understand the features of autoencoders. We’ll also see the step by step by step process of autoencoders and in the end, we’ll see the model types of autoencoders. Let’s rush towards the first topic:
What are Autoencoders?
Autoencoders are the type of neural networks that are used to lear ...
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 ...
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 ...
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 ...
Hi pals! Welcome to the next deep learning tutorial, where we are at the exciting stage of TensorFlow. In the last tutorial, we just installed the TensorFlow library with the help of Anaconda, and we saw all the procedures step by step. We saw all the prerequisites and understood how you can follow the best procedure to download and install TensorFlow successfully without any trouble. If you have done all the steps, then you might be interested in knowing the basics of TensorFlow. No matter if you are a beginner or have knowledge about TensorFlow, this lecture will be equally beneficial for all of you because there is some important and interesting information that not all people know. So, have a look at the topics that will be discussed with you in just a bit.
What is a tensor?
What are ...
