Deep Learning courses

635 Courses

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AI TIME PhD ICLR专场四

Immerse yourself in the AI TIME PhD ICLR专场四, a dedicated session focused on the latest breakthroughs in AI research. This Chinese-language event is part of the prestigious International Conference on Learning Representations (ICLR) and features insightful presentations by talented PhD students. Participants will gain an in-depth understandi.

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AI TIME CVPR 专场三

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AI TIME PhD 华南理工实验室专场一

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AI TIME PhD ICLR专场一

Participate in AI TIME PhD ICLR专场一 to stay at the forefront of artificial intelligence innovation. This specialized lecture series, conducted in Chinese, offers a deep dive into recent advancements showcased at the International Conference on Learning Representations (ICLR). Engage with in-depth discussions and analyses led by experts to.

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AI TIME PhD ICLR专场二

Discover the forefront of artificial intelligence research with AI TIME PhD ICLR专场二, a dedicated lecture series offered in Chinese. This series offers a unique opportunity to engage with advanced topics and discussions surrounding papers presented at the International Conference on Learning Representations (ICLR). Participants will delve int.

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大模型为什么是AI领域的“兵家必争之地”？

通过观看本视频，你将深入了解大模型在人工智能领域中扮演的核心角色。视频用中文详细讲解了大模型的重要性、最近的技术进展，以及这些模型如何对未来的AI创新产生深远影响。加入我们，探索AI发展的最前沿。本课程由XuetangX提供，属于以下类别：人工智能课程机器学习课程深度学习课程神经网络课程 Transformer 架构课程

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AI TIME CVPR 专场四

Delve into a specialized conference session dedicated to Artificial Intelligence and Computer Vision, hosted in Chinese and featuring presentations from leading experts at the Conference on Computer Vision and Pattern Recognition (CVPR). Discover the latest developments and innovative methodologies emerging in the fields of AI and computer vis.

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AI TIME PHD - AAAI 专场二

XuetangX Delve into the latest advancements in artificial intelligence at the AI TIME PHD - AAAI 专场二. This Chinese-language session is your gateway to understanding the forefront of AI research. Attendees will benefit from presentations and discussions led by top researchers, focusing on innovative methodologies and practical applications of.

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AI TIME：ICML科普

Dive into the forefront of artificial intelligence and machine learning with the AI TIME：ICML科普 series. This Chinese-language video series provides detailed coverage on key topics presented at the International Conference on Machine Learning (ICML). Expert explanations bring to life recent research papers and the latest technological advanc.

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2020高校人工智能人才培养论坛

参加2020高校人工智能人才培养论坛，聚焦于高等教育机构中的人工智能人才发展。该论坛采用中文进行，涵盖如何培养AI专业技能的讨论，探索教育策略，并探讨与行业的合作，以便为下一代AI专业人士做好准备。论坛将由XuetangX提供，适合有志于深度学习和机器学习等领域的参与者，尤其是那些在计算机科学和高等教育课程中寻求创新的方法和合作机会的人士。

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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:

Face recognition by the DeepFace system is about 97%, and this result is about the same as that of the average person.

Imitation of human speech by the WaveNet system. This is not reading the text, but composing sentences with accents, without errors in stress and without unnatural pauses.

Making medical diagnoses. For example, determining diabetic retinopathy from photographs of the eyes. The technology is already being used in US medical institutions.

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:

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.

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.

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.

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!