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 ...
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! 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 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 ...
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 ...
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 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 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 ...
Hey buddies! Welcome to the next tutorial on deep learning, in which you are about to acquire knowledge related to Python. This is going to be very interesting because the connection between these two is easy and useful. In the last lecture, we had an eye on the latest and trendiest deep learning algorithms, and therefore, I think you are ready to take the next step towards the implementation of the information that I shared with you. To help you make up your mind about the topics of today, I have made a list for you that will surely be useful for you to understand what we are going to do today.
How do you introduce the Python programming language to a deep learning developer?
How is Python useful for deep learning training in different ways?
Do Python provide the useful frameworks for ...
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 ...
