What makes humans truly remarkable is our ability to perceive, understand, and learn from the world around us. Our brains are really fascinating biological computational models, containing something known as Neurons which count approximately up to 100 billion. With this intricate network of neurons in our brains, we have the capacity to process information, recognize patterns, and make intelligent decisions. It is this exceptional cognitive ability that has inspired scientists and researchers to explore the concept of Artificial Intelligence (AI) and, more specifically, Deep Learning.
Deep Learning, a branch of AI, aims to replicate the remarkable capabilities of the human brain within machines. It seeks to unravel the secrets behind human intelligence and leverage that knowledge to create intelligent systems that can learn, reason, and solve complex problems.
Deep Learning comes with a lot of complex data-driven and architecture-based concepts which are really interesting to learn and a bit hard as well, but, In this tutorial, we'll learn each and every topic related to deep learning its core in a really simple way with examples. We will explore the architecture of neural networks, delve into fundamental concepts such as convolutional and recurrent networks, and uncover advanced techniques like generative adversarial networks and reinforcement learning. Along the way, we will dive into practical implementations, gain insights into state-of-the-art research, and witness the incredible capabilities of Deep Learning models.
This tutorial is constantly updating, and new topics are added, so stay subscribed, you can subscribe simply, by just going to "Info" > "Join".
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