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Artificial Intelligence. Full Course. Artificial Intelligence for BeginnersНазвание: Artificial Intelligence. Full Course. Artificial Intelligence for Beginners
Автор: Pon Mahesh
Издательство: Kindle, Inc.
Год: 2020
Страниц: 229
Язык: английский
Формат: pdf, epub
Размер: 28.0 MB

Artificial Intelligence for beginners. Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term "artificial intelligence" is often used to describe machines (or computers) that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem-solving "In this book, I'll be covering all the domains and the concepts involved under the umbrella of artificial intelligence, and I will also be showing you a couple of use cases and practical implementations by using Python. So, there's a lot to cover in this session.

So, we're gonna begin the session by understanding the history of artificial intelligence and how it came into existence. We'll follow this by looking at why we're talking about artificial intelligence now, why has it gotten so famous right now. Then we'll look at what exactly is artificial intelligence. We'll discuss the applications of artificial intelligence, after which we'll discuss the basics of AI where in we'll understand the different types of artificial intelligence.

We'll follow this by understanding the different programming languages that can be used to study AI. And we'll understand why we're gonna choose Python. Alright, I'll introduce you to Python. And then we'll move on and discuss machine learning. Here we'll discuss the different types of machine learning, the different algorithms involved in machine learning, which include classification algorithms, regression algorithms, clustering, and association algorithms.

To make you understand machine learning better, we'll run a couple of demos wherein we'll see how machine learning algorithms are used to solve real world problems. After that, we'll discuss the limitations of machine learning and why deep learning is needed. I'll introduce you to the deep learning concept, what are neurons, perceptron’s, multiple layer perceptron’s and so on. We'll discuss the different types of neural networks, and we'll also look at what exactly back propagation is. Apart from this, we'll be running a demo to understand deep learning in more depth. And finally, we'll move onto the next module, which is natural language processing.

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