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! I hope you are doing great. Today, we will talk about another modern neural network named gated recurrent units. It is a type of recurrent neural network (RNN) architecture but is designed to deal with some limitations of the architecture so it is a better version of these. We know that modern neural networks are designed to deal with the current applications of real life; therefore, understanding these networks has a great scope. There is a relationship between gated recurrent units and Long Short-Term Memory (LSTM) networks, which has also been discussed before in this series. Hence, I highly recommend you read these two articles so you may have a quick understanding of the concepts.
In this article, we will discuss the basic introduction of gated recurrent units. It is better ...
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 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 ...
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 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 ...
Hello students, welcome to the second tutorial on deep learning in the first one, we have learned the simplest but basic introduction of deep learning to have a solid base about what we are actually going to do with deep learning. In the present lecture, we will take this to the advanced level and will learn the introduction with the intention of learning more and more about the introduction and understanding what we want to learn and how will we implement the concepts easily. So, here is a quick glance at the concepts that will be cleared today:
What do we mean by Deep learning?
What is the structure of calculation in neural networks?
How can you examine the Neural Networks?
What are some platforms of deep learning?
Why did we choose TensorFlow?
How can you work with TensorFlow?
...
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 ...
Hey learners! Welcome to the new tutorial on deep learning, where we are going deep into the learning of the best platform for deep learning, which is TensorFlow. Let me give you a reminder that we have studied the need for libraries of deep learning. There are several that work well when we want to work with amazing deep-learning procedures. In today’s lecture, you are going to know the exact reasons why we chose TensorFlow for our tutorial. Yet, first of all, it is better to present the list of topics that you will learn today:
Why do we use TensorFlow with deep learning?
What are some helpful features of this library?
How can you understand the mechanism of TensorFlow?
Show the light towards the architecture, and components of the TensorFlow.
In how many phases you can complete t ...
Hello friends, I hope you all are having fun. Today, we are bringing you one of the most advanced and trending courses named "Deep Learning". Today, I am sharing the first tutorial, so we will discuss the basic Introduction to Deep Learning, and in my upcoming lectures, we will explore complex concepts related to it. Deep Learning has an extensive range of applications and trends and is normally used in advanced research. So, no matter which field you belong to, you can easily understand all the details with simple reading and practicing. So without any further delay, let me show you the topics that we are going to cover today:What is deep learning?What are artificial intelligence and machine learning?Working with deep learning using neural networks.Trends in deep learning.Deep learning as ...
