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Transformer Neutral Network in Deep Learning
Transformer Neutral Network in Deep Learning, Transformer Neutral Network working, Transformer Neutral Network applications, Transformer Neutral Network in Deep Learning definition
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 ...
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Introduction to Quantum Computing
what is quantum computing, quantum computing types, quantum computing algorithms, quantum computing applications, quantum computing future
Hi readers! I hope you’re having a great day and finding something thrilling. Imagine being able to solve a problem in seconds that would take the fastest supercomputers millennia, that is, quantum computing. Today, we will cover Quantum Computing. Quantum computing is a relatively new technology that can present a new way of thinking about how information may be processed using the laws of quantum mechanics. Classical computing uses bits, which are either 0 or 1, while processing information, whereas quantum computing uses qubits and has the possibility of being a bunch of things at the same time by virtue known as the “superposition”. In addition to "superposition", qubits can be connected across space through a property known as "Entanglement", which allows quantum computers the potent ...
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Latest Deep Learning Frameworks
latest deep learning framework, deep learning framework, top deep learning framework, pytorch deep learning, keras deep learning, tensorflow deep learning
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 ...
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Vision Transformer Neural Network Architecture
Vision Transformer Neural Network Architecture, Vision Transformer Neural Network Network
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 ...
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Deep Q Networks (DQN) Reinforcement Learning
Deep Q Networks (DQN) Reinforcement Learning, dqn neural network, deep Q basics, deep Q working
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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Basics of TensorFlow for Deep Learning
Basics of TensorFlow for Deep Learning, tensorflow deep learning, deep learning tensorflow, deep learning python, python deep learning
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 ...
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Capsule Neural Network: Definition, Features, Algorithms, Applications
Basic Concepts of Capsule Neural Network, Capsule Neural Network, Capsule NN, Capsule Neural Network examples, Capsule Neural Network types
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 ...
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EfficientNet Neural Network: Definition, Working, Features
EfficientNet Neural Network, EfficientNet Neural Network working, EfficientNet working, EfficientNet features, EfficientNet deep learning, EfficientNet features
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 ...
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Introduction to Quantum Tunneling
Introduction to Quantum Tunneling, what is Quantum Tunneling, Quantum Tunneling Applications, Quantum Tunneling key features, the Schrödinger Equation
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 ...
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Getting Started with TensorFlow for Deep Learning
Getting Started with TensorFlow for Deep Learning, TensorFlow for Deep Learning, Deep Learning TensorFlow, Dataflow Graphs in TensorFlow
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 ...