Deep Learning courses

635 Courses

XuetangX

人工智能基础

本课程全面介绍了人工智能的基础原理，涵盖四大方面：搜索与问题求解、知识与推理、学习与发现以及具体应用领域。搜索与问题求解涉及问题解决的基本原理、策略与图搜索以及博弈；知识与推理涵盖谓词逻辑、归结原理与确定性推理；学习与发现部分涉及机器学习知识，包括分类、回归和聚类算法；深度学习入门涉及图像识别、卷积神经网络、自然语言处理及循环神经网络。通过本课程.

XuetangX

智能车辆理论与应用

课程内容涵盖智能车辆的各个方面，如环境感知技术、深度学习及其在智能车辆上的应用、智能车辆SLAM、行为决策和运动规划等关键领域。特别介绍了智能网联技术以及智能车辆的测评体系。本课程是国内较早开设的研究生课程，“智能车辆理论与技术”是北京理工大学机械工程学科的核心课程，通过丰富的案例理论联系实际进行讲解。

XuetangX

现代光电图像处理方法

本课程是专业必修项目，提供32学时的校内讲授，面向学术和专业硕士研究生，每年约有60名学生参与。课程重点在于现代光电成像技术及其图像处理方法，采用专题模块的讲授形式。每个专题全面覆盖从基本原理到理论方法，再到典型应用分析，旨在帮助学生融会贯通本科阶段所学课程，同时塑造工科思维。此外，课程紧跟技术发展前沿，重点反映当前光电图像处理方法的最新进展，拓.

XuetangX

Delve into the forefront of artificial intelligence and machine learning research during the AI TIME PhD ICLR专场六 session. This expertly curated event brings together leading minds in academia and industry to explore and discuss cutting-edge topics, all delivered in Mandarin. Attendees will gain valuable insights into recent advancements in ne.

XuetangX

Chalmers University of Technology

人工智能与医学数据计算

《人工智能与医学数据计算》课程共分为十节课。课程从人工智能与医学数据计算的背景知识入手，提供人工智能和深度学习的发展概述。第二课分析人工智能目标，介绍关键技术及相关概念，重点解析两种不同人工智能技术的区别与联系。第三和第四节课概述人工智能的基本应用场景及操作环境的软硬件要求，为后续的深度学习关键技术学习奠定基础。第五节课关注深度学习网络架构，.

XuetangX

计算机是如何实现智能的

Join a captivating Chinese language lecture by Tsinghua University, delving into how computers achieve intelligence. This course uncovers the foundational concepts of artificial intelligence and computer intelligence, highlighting the processes of information processing, decision making, and the simulation of human cognitive functions. Learn.

XuetangX

Udemy

Complete Python and Machine Learning in Financial Analysis

Udemy offers an extensive course titled "Complete Python and Machine Learning in Financial Analysis" that combines practical use of Python with advanced Machine Learning and Deep Learning methods tailored for financial analytics. This course is structured with step-by-step coding instructions alongside all required codes, enhancing your skills i.

Udemy

Complete A.I. & Machine Learning, Data Science Bootcamp

Dive into the world of A.I. and machine learning through this thorough Data Science Bootcamp. Master the essentials of data analysis and machine learning using Python, TensorFlow, and Pandas. Join our course, provided by Udemy, and leverage expert insights into deep learning and data visualization. This bootcamp caters to a wide range of inte.

Udemy

TensorFlow for Deep Learning Bootcamp

TensorFlow for Deep Learning Bootcamp | Udemy Enroll in the TensorFlow for Deep Learning Bootcamp offered by Udemy and elevate your skills in Artificial Intelligence, Machine Learning, and Deep Learning. This comprehensive course is designed to provide you with hands-on experience and in-depth knowledge using TensorFlow, Google's powerful open-so.

Udemy

TensorFlow: Machine Learning e Deep Learning com Python

Udemy

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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!