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Neural Network Courses

305 Courses

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

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

系列综述带你了解ChatGPT、AIGC和扩散模型

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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, Neuronale Netze und TensorFlow in Python

Werde ein Experte im Deep Learning mit diesem umfassenden Kurs zur Mathematik und Praxis neuronaler Netze, unter Verwendung von Keras und TensorFlow in Python. Diese 2024 Edition bietet aktuelle Inhalte und praktische Einblicke in die Welt des Machine Learnings.
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California Institute of Technology XuetangX

Introduction to Artificial Intelligence

Gain a comprehensive understanding of artificial intelligence with our extensive course, incorporating knowledge from diverse fields such as philosophy, brain science, mathematics, and computing. This program delves into various AI types, including perceptual, cognitive, language, and behavioral intelligence. Discover fundamental concepts and st.
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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!