Neural Network Courses

305 Courses

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 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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人工智能技术

近年来在大数据、云计算、物联网等信息环境推动以及新的算法、模型和硬件助力下,人工智能在自然语言理解、语音识别、视觉分析和数据挖掘等领域取得了显著进展,成为社会经济发展的引擎。人工智能作为计算机科学的一个重要分支,是一门理论基础完善、多学科交叉且应用领域广阔的前沿学科,主要研究如何利用计算机模拟、延伸和扩展人类的智能行为。《人工智能技术》课程是计算.
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小白学人工智能

中国也在大力发展新一代人工智能技术,并致力于将其应用于各行各业。本课程完成后,学生将能够: 了解人工智能行业的最新应用和发展趋势。 从数据、算法和计算力的角度理解人工智能的发展。 用行业或生活术语比喻人工智能的概念和原理。 体验和理解深度学习原理,涉及CNN、图像风格迁移、RNN等架构。 通过实例理解深度学习特征,如输入层、隐藏层、输.
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人工智能

本课程的特色包括: 注重人工智能核心技术体系的构建,讲解全面完整,涵盖多个核心技术途径,如机器学习和神经网络等。 从“认识你自己”角度出发,将内容有机结合为一个整体,便于系统理解和掌握。 培养解决实际问题的思路,通过案例示例展示基本思路。 注重人工智能思维模式的建构,强调技术与非技术的区别。 注重技术创新思维的培养和建构。 本课程自2008年起.
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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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Who is a neural network developer?

A neural network developer designs and programs hardware and software systems that operate on the principle of the human brain (neural networks).

Introduction to Neural Network Courses

A neural network developer is a programmer who creates software for mathematical models that work on the principle of the nervous system of a living organism.

A neural network is a computer programme built on the model of the structure and functioning of the human brain. Its constituent artificial neurons are tiny mathematical functions that perform computational actions - receive information, process and compare it, and pass it on. A neural network is not programmed in the usual sense of the word once and for all - it learns by loading and constantly processing huge data sets. For this purpose, special algorithms are used, which are created by the neural network developer. As a result, an artificial neural network can compare data, find patterns and on their basis make its own conclusions, classify information, predict events, recognise images, speech.

The task of a neural network developer is to create a programme capable of learning and teach it to learn. Examples of the results of neural network developers' work after neural network courseі include chatbots, voice assistants, text generators, mobile applications capable of recognising faces in photos or emotions in videos, navigation systems for unmanned cars, systems for detecting faults during maintenance, etc.

Career Paths and Learning Paths

Since, by and large, the creation of neural networks is one of the narrow specialisations of a Data Science specialist, the core knowledge of a neural network developer is Big Data science (data modelling, quality assessment of algorithms and prediction models). Also included in the knowledge pool are:

A lot of lectures on neural networks can be found on YouTube. Often after the video, machine learning enthusiasts do a detailed breakdown of the material. There are tutorial applications on the Internet (like artificial neural network course) with ready-made architectures that clearly demonstrate what is happening inside a neural network and give instructions on how to build it into a specific project.

Course Benefits and Features

Let's take a look at the main pluses of the neural networks and deep learning courseі:

These are just some of our advantages.

Enrollment Process

You can email us and sign up for our online lessons now. You can take a deep neural network course on one of the educational platforms. These courses are designed for people with no particular background, so they are suitable for most people. Online training is usually focused on practice - this allows you to quickly build up your portfolio and get a job immediately after training!