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Deep Learning courses

591 Courses

California Institute of Technology Coursera

Dönüştürücü Modelleri ve BERT Modeli

Bu kurs, dönüştürücü mimarisi ve çift yönlü kodlayıcı temsilleri (BERT) modeline dair kapsamlı bir inceleme sunmaktadır. Öz dikkat mekanizması gibi dönüştürücünün ana bileşenlerini öğrenme fırsatı bulacak, BERT modelini oluşturmak ve bu modeli çeşitli görevlerde kullanmak için dönüştürücünün nasıl uygulandığını keşfedeceksiniz. Sınıflandırma,.
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California Institute of Technology XuetangX

初识《神经网络理论及应用》——之课程知多少？

Join the introductory lecture on neural networks presented by Beijing Technology and Business University. This course is designed to provide foundational knowledge about artificial neural network concepts, theoretical frameworks, and their practical applications. Perfect for those eager to explore the world of neural networks, this lecture.
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California Institute of Technology XuetangX

智能控制技术

本课程体系简约而全面，逐步讲解智能控制技术，内容配有例题与习题，助力学生深入理解与掌握核心概念。课程共有七章，包含34节课。 第一章为绪论，介绍智能控制的发展历程及主要方法，分析智能控制系统的构成原理，共3节课。第二章探讨模糊控制的理论基础，从模糊集合、运算、隶属度函数到模糊逻辑推理进行详细讲解，重点在模糊集数学理论，共7节课。 第三章解析模糊控制系统.
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California Institute of Technology Northeastern University

人工智能

《人工智能》课程的主要特点包括以下几个方面： 门槛较低：不需要掌握计算机基础知识，只需大学工科数学基础和一门编程语言。 内容全面：涵盖经典人工智能技术、机器学习及深度学习相关知识，系统介绍发展历程中的各种成果和走过的弯路。 实践性强：不仅提供理论讲授，还有编程实践，学生普遍对这部分内容非常感兴趣。 本课程适合希望全面了解和掌握人工智能技术.
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California Institute of Technology XuetangX

清华大学计算机科学与技术系六十周年系庆学术报告（三）人工智能

六十周年系庆学术报告是清华大学计算机系建系六十周年的庆祝活动之一。组织这一系列学术报告的目的是：通过邀请国内外学术界与产业界知名的学者、专家做专题演讲，介绍国际前沿研究及产业发展动向，分享他们的战略思考与成果，实现在交流中找到差距，明确方向，从而促进清华大学计算机学科进一步向前发展。 六十周年系庆学术报告是一场学术盛宴。报告的演讲者都是各个领域的.
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California Institute of Technology AWS Skill Builder

AWS Flash - Dar rienda suelta a la innovación: la revolución de la IA generativa (Español LATAM) | AWS Flash - Unleashing Innovation: The Generative AI Revolution (LATAM Spanish)

Descubra cómo la inteligencia artificial generativa transforma la innovación creativa más allá de la simple novedad. Este curso básico de 2 horas le proporcionará un conocimiento accesible de cómo utilizar esta tecnología de manera colaborativa y responsable para impulsar la innovación. Nivel del curso: básico Duración: 2 horas Actividades.
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California Institute of Technology Coursera

AI Foundations for Everyone

Artificial Intelligence (AI) is reshaping industries and influencing our daily lives. This specialization is crafted for individuals from all walks of life, whether you're a tech guru or a novice, focusing on the impact and potential of AI on society and organizations. No prior programming knowledge is required. The course is designed to prov.
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California Institute of Technology Northeastern University

Foundations in Human-Centered AI

Join us for the Foundations in Human-Centered AI course, where we delve into a critical area of artificial intelligence research focused on enhancing and augmenting human capabilities. Instead of seeking to replace human skills, this course concentrates on designing AI technologies that work with and for humans. Our journey begins with a histo.
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California Institute of Technology University of California, San Diego

Deep Learning For Visual Computing

Deep learning revolutionizes how machines understand data by leveraging non-linear transformation architectures to solve hierarchical recognition tasks. Imagine a machine recognizing Mr. X in a photo standing before Mt. E; features evolve from identifying shapes, colors, and edges to comprehending complex scenes and objects. This course will.
California Institute of Technology Coursera

IBM Generative AI Engineering

Embark on a transformative learning journey with the IBM Generative AI Engineering Professional Certificate, an opportunity tailor-made for aspiring generative AI engineers, AI developers, data scientists, machine learning engineers, and AI research engineers. With the generative AI market poised for a significant growth of over 46% CAGR until.
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Artificial intelligence is moving towards becoming on the same level as the living human mind. In such dangerous proximity to the execution of one of the futurological scenarios, it becomes a little scary, but at the same time very interesting. Artificial intelligence is nurtured by machine learning specialists. In the last decade, the deep learning method has been developing, and its results are already impressive.

What is deep learning?

“Deep learning” – literally “deep learning”. This is about artificial intelligence and increasing its abilities through training, based not on artificial codes, but on principles similar to the development of human intelligence. Deep learning methods make it possible to make machines self-learning.

The term itself and developments in this area appeared 40 years ago, but until 2012 they could not be applied in practice, as they were limited by insufficient technical capacity. Now there are already published works by the pioneers of deep learning, and textbooks and training courses in this specialty are gradually appearing.

Deep learning on your fingers: The ability of a machine to find an answer using calculations is called artificial intelligence. A machine can be taught to learn independently by building appropriate algorithms - this is called machine learning. With this approach, coded algorithms will no longer be needed to solve problems. The process of acquiring and using skills imitates human thinking and is called deep learning.

What tasks can be performed using deep learning right now?

If at the dawn of automation machines learned to do mechanical work for humans, now machines are learning to do routine intellectual work for us. The further progress we make, the more tasks we can shift to them, freeing up time for what really matters.

Officially, the main task of deep learning is the automation of complex tasks in various areas of human activity. It's like a computer, only of a different century and a different level.

But of particular interest is the neural network’s assistance in creating programs for solving cognitive problems.

Enough general phrases, let's move on to examples:

It’s hard to even imagine what awaits us in the future if people outside of IT have just heard about deep machine learning, and it has already produced such amazing results.

Why study deep learning?

To earn twice as much as ordinary IT specialists. Progress in the field of information technology is not just walking, but actually running, and it’s time to benefit from it. The sphere is not yet oversaturated, and oversaturation will not happen soon. Still, creating neural networks is not as simple as filing nails or maintaining Instagram accounts. But now is the time to start studying in order to develop along with your specialty and, perhaps, soon become someone who develops it.

Deep learning courses that currently exist are divided into four categories. Decide for yourself which one is for you:

  1. Trainings are highly specialized classes for practicing specific skills. Suitable for those who need to form an understanding of the basic principles of machine thinking.

  2. Long courses - for AI specialists and those involved in database analysis. Long-term deeplearning ai courses are not for everyone and require patience and time.

  3. University programs - for maximum immersion in the subject. They may be too difficult for beginners, although the application of effort will give results that should not be expected from short courses.

  4. A short best deep learning course on technology in business - general information for managers who will not be doing it themselves, but need to have an understanding of the subject.

You will have to put in a lot of effort, but the result is worth it. Just for fun, you can look at vacancies for deep learning specialists on sites with job offers and evaluate upcoming prospects. Not everyone needs deep learning experience yet, and soon all the sweet jobs will require several years of practice. So, if you have the ability to train soulless machines that are almost equal to us in intelligence, hurry up to take up vacant positions after a deep learning online course from AI Eeducation!