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Deep Learning courses

487 Courses

California Institute of Technology XuetangX

深度学习

本课程主要面向计科、人工智能及物联网专业的本科生，讲述深度学习基本概念、经典深度学习模型及其实践，主要内容包括前馈神经网络、深度模型优化与正则化、卷积神经网络、循环神经网络等，并介绍深度学习框架的编码实现和参数优化方法。本课程注重理论学习与实践应用的结合，除了课堂讲授之外，还将通过实践环节引导学生使用深度学习平台或工具，让学生通过实际应用来加深.
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California Institute of Technology XuetangX

人工智能与生物特征识别

课程名称：人工智能与生物特征识别 课程描述：本课程为专业选修课程，北京理工大学研究生精品课程，学时为32学时，向研究生及高年级本科生开放。课程通过理论与实践的结合，强化学生在相关领域的能力。基于本课程，历届学生成绩显著，多次在中国研究生电子竞赛中斩获全国及区域多项大奖。课程优势在于全面介绍智能成像与信息感知技术，结合机器学习和深度学习技术，指导学.
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California Institute of Technology XuetangX

基于图神经网络的事实验证

加入这场由XuetangX提供的中文讲座，探索如何利用图神经网络进行有效的事实验证。该课程专注于图形深度学习方法的应用，以自动化执行事实检查和验证的任务。参与者将有机会学习如何构建知识图谱、实现图神经网络架构，并通过分析结构化知识库中的实体与证据之间的关系来判定主张的准确性。 该课程特别适合对深度学习、神经网络和知识图谱领域感兴趣的学习者，希望深入.
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California Institute of Technology XuetangX

万物互联

庄子曾言：“圣人者，原天地之美而达万物之理”。他通过对天地壮美的感受洞悉了宇宙万物的演化规律。随着科技的发展，感知设备能够更加智能地连接人与信息，把现实与数字世界无缝衔接，万物互联的新时代即将开启。我们的课程将引领你进入这个高能的万物互联时代。 课程沿时间线梳理万物互联的发展历程，深入讲解互联网的不同发展阶段，细致剖析万物互联的事物、数据、人员和流程.
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California Institute of Technology XuetangX

人工智能通识

2017年7月，中国国务院发布了《新一代人工智能发展规划》，将人工智能的发展提升为国家战略。这不仅有力支撑了高质量发展，还丰富了新生产力内涵，成为衡量国家科技创新和高端制造水平的关键指标。 西南交通大学计算机与人工智能学院推出的《人工智能》通识课程引领您探索推动第四次工业革命的人工智能技术。本课程自2017年开设以来，已成为全国高校中最早的人工智能教学.
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California Institute of Technology XuetangX

融合知识的预训练语言模型

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California Institute of Technology XuetangX

人工智能导论

人工智能导论 人工智能技术在各行业中扮演着日益重要的角色，通过推动经济和社会的高质量发展，极大地改变着人们的生活方式，包括衣食住行、工作学习以及娱乐休闲。智能设备、无人驾驶、语音助手、推荐系统等新兴产品为我们的日常生活增添了全新的体验。 人工智能的起源可追溯至计算机科学，为解决复杂问题而生。随着技术的演进，人工智能经历了符号主义到深度学习的多个发.
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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

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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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!