Neural Network Courses

305 Courses

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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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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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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Principles and Practice of Artificial Intelligence

In July 2017, China's State Council unveiled the "New Generation Artificial Intelligence Development Plan," a pivotal move that positioned AI advancement as a national strategic focus. As AI drives high-quality development, it reshapes the concept of new productive forces and stands as a measure of a nation's technological innovation and prowess in.
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Introduction to Artificial Intelligence(人工智能导论)

Explore the fundamentals of artificial intelligence with our comprehensive course, "Introduction to Artificial Intelligence(人工智能导论)." This course, delivered by XuetangX, covers five insightful chapters designed for learners keen on understanding AI's core concepts and applications. Chapter 1: Introduction to Artificial Intelligence In.
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【試験対策から本質の理解まで、知識をまとめて身に付けよう!】G検定対策講座

イベントタイトル:試験対策から本質の理解まで、知識をまとめて身に付けよう!G検定対策講座 概要:G検定は機械学習やディープラーニングの基礎を学ぶための重要な入口となる試験です。この講座では、受験対策として知識をまとめ、本質的な理解を深められるようにサポートします。 プラットフォーム:Udemy 関連カテゴリー:人工知能コース、機械学習コース、ディープラー.
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Intelligent Control(智能控制)

The rise and in-depth research of artificial intelligence propel control theory toward simulating various intelligences. Concurrently, the automatic control of unmanned systems and intelligent products drives continuous development in intelligent control technology. This course serves as a professional core for students majoring in automation, c.
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All of AI: ChatGPT, Midjourney, Stable Diffusion & App Dev

Find this AI course on Udemy Explore various aspects of artificial intelligence, from ChatGPT and prompt engineering to OpenAI API and beyond. This course covers diverse topics such as AI app development, chatbots, GPTs, and machine learning. Get hands-on experience with generative AI, automation, and copilot functionalities. Perfect for anyon.
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Cloud Computing and Artificial Intelligence

This course covers the structure and possibilities of Cloud Computing, emphasizing the merging of data with AI services like IoT, key technologies in the Fourth Industrial Revolution. It also delves into the applications of big data processing through text analytics. Participants will gain an understanding and practical skills in the principles o.
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人工智能导论

探索人工智能基础概念,研究数据驱动的网络模型、算法与平台。本课程梳理人工智能的关键发展节点,激发您的学习兴趣。通过此课程,您将牢牢掌握人工智能基础,为深度学习的最前沿铺路,不仅适合计算机专业学生,也对其他学科的学生适宜。
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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!