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 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 ...
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 ...
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 ...
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 pupils! Welcome to the next session of the neural network series. I hope you are doing good. In the previous part of this series, I showed the double deep Q networks and discussed their differences from the deep Q network to make things clear. Today, I am going to visit a very popular neural network with you. This is the spiking neural network that mimics the functionality of the biological neurons with the help of spikes. This is a different neural network than the traditional networks and you will see the details of each point.
In this lecture, we’ll understand the introduction of the spiking neural network. We’ll discuss all the basic terms that are used while studying the SNN. After that, we’ll move on to the steps of using SNN in detail. In the end, we’ll move towards the appl ...
Hi readers! Hopefully, you are doing well and exploring something fascinating and advanced. Imagine that particles can pass through walls but not by breaking them down? Yes, it is possible. Today, we will study Quantum Tunneling.
Quantum tunneling may be one of the strangest and illogical concepts of quantum mechanics. Quantum Tunneling proves the phenomenon of particles like electrons, protons, or even whole atoms percolating through the energy barrier of potential energy, although they do not appear to have sufficient potential to slide over it. The classical physics version of this ball at this point would merely reverse.
Nevertheless, in the quantum realm of things, particles now act like waves, and waves can pass through and even over barriers with some nonzero probability of the pa ...
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 readers! Welcome to the next episode of the Deep Learning Algorithm. We are studying modern neural networks and today we will see the details of a reinforcement learning algorithm named Deep Q networks or, in short, DQN. This is one of the popular modern neural networks that combines deep learning and the principles of Q learning and provides complex control policies.Today, we are studying the basic introduction of deep Q Networks. For this, we have to understand the basic concepts that are reinforcement learning and Q learning. After that, we’ll understand how these two collectively are used in an effective neural network. In the end, we’ll discuss how DQN is extensively used in different fields of daily life. Let’s start with the basic concepts.
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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 ...
