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 ...
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 ...
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 Learners! Welcome to the next lecture on deep learning. We have read the detailed introduction to deep learning and are moving forward with the introduction of the neural network. I am excited to tell you about the neural network because of the interesting and fantastic applications of neural networks in real life. Here are the topics of today that will be covered in this lecture:
What do we mean by the neural network?
How can we know about the structure of the neural network?
What are the basic types of neural networks?
What are some applications of these networks?
Give an example of a case where we are implementing neural networks.
Artificial intelligence has numerous features that make it special and magical in different ways, and we will be exploring many of them in dif ...
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 ...
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 ...
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 ...
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 ...
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 ...
