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Deep Learning courses

487 Courses

California Institute of Technology XuetangX

走进人工智能（人工智能概论）

走进人工智能（人工智能概论）课程是一门专为高职专科生设计的课程，旨在帮助学习者了解并感知人工智能技术在日常生活中的应用。课程设计理念通过将复杂的技术理论与实际应用场景结合，以便学习者通过生活感知人工智能，并通过视频、图文、讨论等多元化形式激发兴趣。学习者还可以通过作业和考试环节加深理解和巩固学习成果。 课程涵盖七大模块，包括：人工智能的发展历史、.
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California Institute of Technology XuetangX

机器学习入门

欢迎加入系统、科学且专业的机器学习入门课程。这门课程不仅涵盖传统的机器学习内容，还包括了深度学习的先进知识。您将学习到机器学习和深度学习的基础理论、算法原理及数据处理技巧，并且通过实际案例分析提高自己的实践能力，从而为未来的学习和职业发展奠定坚实基础。 这是一门针对机器学习初学者设计的课程，涵盖广泛的基本知识，适合各专业背景的学生参与学习。无论您的.
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California Institute of Technology XuetangX

论文一作学者分享大模型前沿研究

论文一作学者分享大模型前沿研究 Discover the forefront of AI advancement by learning about the latest developments in large language models from a lead research author. This Chinese-language academic presentation offers a unique opportunity to acquire deep technical understanding of current research directions, innovative methodological approac.
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California Institute of Technology XuetangX

人工智能（通识课）

人工智能在互联网时代获得了前所未有的发展机遇，已经成为目前发展最迅速、对社会影响最大的新兴学科。由于人工智能是模拟人类智能解决问题的方法，几乎在所有领域都具有非常广泛的应用，所以，目前许多高校开设了大学生人工智能通识课程。 课程涵盖了人工智能的概念、发展简史、研究内容及应用，引导学生深入各个研究领域，并介绍知识表示、推理方法、搜索策略、遗传算.
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California Institute of Technology XuetangX

AI TIME：深度推荐系统的探索与实践

AI TIME: 深度推荐系统的探索与实践 Delve into the world of deep recommendation systems with our in-depth lecture conducted in Chinese, brought to you by XuetangX. This course offers a comprehensive exploration of both the theoretical underpinnings and practical implementations of recommendation algorithms. Engage with key concepts and examine how.
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California Institute of Technology XuetangX

初探人工智能

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California Institute of Technology XuetangX

人工智能技术与应用

This course is tailored for engineering management graduate students, integrating artificial intelligence theory, experiments, and engineering practice. Theoretical topics include an introduction to AI, knowledge representation and graphs, search strategies, genetic algorithms, swarm intelligence, neural networks, machine learning, deep learni.
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California Institute of Technology XuetangX

基于神经网络模型的开放领域对话系统研究

参与这次由XuetangX提供的中文讲座，深入研究基于神经网络的开放领域对话系统。在此次课程中，您将探索自然语言处理的核心概念、深度学习架构以及能够实现与人类相似互动的会话式人工智能技术。这个课程是为希望提升自己在机器学习、深度学习及相关领域技能的学习者设计的。
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California Institute of Technology XuetangX

微软--计算机视觉论文分享课

随着云计算、大数据和机器学习的迅速发展，计算机视觉作为人工智能领域的核心技术之一，近年来取得了诸多突破性进展。如今，不论是在学术界、工业界，还是在初创企业中，计算机视觉都备受关注！CVPR会议是由IEEE主办的计算机视觉和模式识别领域的顶级会议。为了推动国内计算机视觉研究的发展，强化工业界与学术界的交流，微软亚洲研究院主办，清华大学媒体与网络技术教育部-微.
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California Institute of Technology Udemy

Deep Learning ve Python: A'dan Z'ye Derin Öğrenme (5)

Python ile Derin Öğrenme algoritmaları geliştirerek yapay zeka alanında bir adım daha öne çıkın. Bu kurs, 2020 yılında Udemy tarafından sunularak, katılımcılarına modern yapay zeka uygulamaları geliştirme konusunda kapsamlı bir bilgi sunmaktadır. Kategori: Yapay Zeka Kursları Kategori: Python Kursları Kategori: Derin Öğrenme Kursları K.
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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!