Neural Network Courses

305 Courses

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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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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人工智能

人工智能是计算机科学的一门前沿与交叉学科,本课程全面介绍人工智能的基础理论和基本技术。通过本课程的学习,要求学生能够了解人工智能的发展及其研究领域;掌握知识表示的各种方法,基本的问题求解技术以及基本的推理技术;并理解人工神经网络的基本结构和学习方法且能够初步理解专家系统、机器学习、自然语言处理等应用领域的知识。 提供者: XuetangX 类别: 人工智能课.
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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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智能控制

了解智能和智能控制的基本概念,掌握智能控制发展历史及其在各领域的应用。课程内容涵盖专家系统、模糊控制、神经网络和进化计算的基础知识,介绍这些算法的仿真实现方法及其在实际工程中的应用。
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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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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 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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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!