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    • Nlp

    筛选依据

    ''nlp'的 338 个结果

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      DeepLearning.AI

      Natural Language Processing

      您将获得的技能: Machine Learning, Natural Language Processing, Statistical Programming, Python Programming, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Data Science, Statistical Machine Learning, Probability & Statistics, Algorithms, Bayesian Statistics, Communication, Computer Graphics, Computer Programming, Dimensionality Reduction, Experiment, General Statistics, Human Computer Interaction, Machine Learning Software, Markov Model, Mathematics, Operations Research, Regression, Research and Design, Strategy and Operations, Theoretical Computer Science, User Experience

      4.6

      (4.9k 条评论)

      Intermediate · Specialization · 3-6 Months

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      DeepLearning.AI,Stanford University

      Machine Learning

      您将获得的技能: Machine Learning, Probability & Statistics, Machine Learning Algorithms, General Statistics, Theoretical Computer Science, Algorithms, Applied Machine Learning, Artificial Neural Networks, Regression, Econometrics, Computer Programming, Deep Learning, Python Programming, Statistical Programming, Mathematics, Tensorflow, Data Management, Data Structures, Statistical Machine Learning, Reinforcement Learning, Probability Distribution, Mathematical Theory & Analysis, Data Analysis, Data Mining, Linear Algebra, Computer Vision, Calculus, Feature Engineering, Bayesian Statistics, Operations Research, Research and Design, Strategy and Operations, Computational Logic, Accounting, Communication

      4.9

      (8.1k 条评论)

      Beginner · Specialization · 1-3 Months

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      DeepLearning.AI

      Deep Learning

      您将获得的技能: Deep Learning, Machine Learning, Artificial Neural Networks, Python Programming, Statistical Programming, Machine Learning Algorithms, Linear Algebra, Applied Machine Learning, Statistical Machine Learning, Dimensionality Reduction, Feature Engineering, Probability & Statistics, Business Psychology, Entrepreneurship, Machine Learning Software, Computer Vision, Marketing, General Statistics, Natural Language Processing, Computer Programming, Leadership and Management, Project Management, Regression, Sales, Strategy, Strategy and Operations, Tensorflow, Differential Equations, Mathematics, Applied Mathematics, Decision Making, Supply Chain Systems, Supply Chain and Logistics, Advertising, Communication, Estimation, Forecasting, Mathematical Theory & Analysis, Statistical Visualization, Algorithms, Theoretical Computer Science, Bayesian Statistics, Calculus, Probability Distribution, Statistical Tests, Big Data, Computer Architecture, Computer Networking, Data Management, Human Computer Interaction, Network Architecture, User Experience, Algebra, Computational Logic, Computer Graphic Techniques, Computer Graphics, Data Structures, Data Visualization, Hardware Design, Interactive Design, Markov Model, Network Model

      4.8

      (137.8k 条评论)

      Intermediate · Specialization · 3-6 Months

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      DeepLearning.AI

      Natural Language Processing in TensorFlow

      您将获得的技能: Machine Learning, Natural Language Processing, Deep Learning, Tensorflow, Artificial Neural Networks, Data Science, Machine Learning Algorithms, Statistical Machine Learning, Applied Machine Learning, Computer Programming, Python Programming, Statistical Programming

      4.6

      (6.1k 条评论)

      Intermediate · Course · 1-4 Weeks

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      Coursera Project Network

      Fine Tune BERT for Text Classification with TensorFlow

      您将获得的技能: Applied Machine Learning, Computer Programming, Deep Learning, Machine Learning, Natural Language Processing, Python Programming, Statistical Programming, Tensorflow

      4.6

      (168 条评论)

      Intermediate · Guided Project · Less Than 2 Hours

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      DeepLearning.AI

      Natural Language Processing with Classification and Vector Spaces

      您将获得的技能: Data Science, Machine Learning, Machine Learning Algorithms, Natural Language Processing, Python Programming, Statistical Programming, Bayesian Statistics, Computer Programming, Deep Learning, Dimensionality Reduction, Experiment, General Statistics, Machine Learning Software, Mathematics, Probability & Statistics, Regression

      4.6

      (3.8k 条评论)

      Intermediate · Course · 1-4 Weeks

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      Coursera Project Network

      NLP: Twitter Sentiment Analysis

      您将获得的技能: Computer Programming, Machine Learning, Natural Language Processing, Python Programming, Statistical Programming, Data Management

      4.6

      (337 条评论)

      Beginner · Guided Project · Less Than 2 Hours

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      Google Cloud

      Advanced Machine Learning on Google Cloud

      您将获得的技能: Machine Learning, Cloud Computing, Google Cloud Platform, Cloud Platforms, Probability & Statistics, Business Psychology, General Statistics, Deep Learning, Entrepreneurship, Statistical Programming, Apache, Cloud Applications, Data Management, Machine Learning Software, Natural Language Processing, Python Programming, Reinforcement Learning, Tensorflow, Artificial Neural Networks, Computer Vision, Performance Management, Strategy and Operations, Applied Machine Learning, Cloud API, Computational Thinking, Computer Architecture, Computer Programming, Data Analysis, Data Engineering, Distributed Computing Architecture, Hardware Design, Machine Learning Algorithms, Other Cloud Platforms and Tools, Theoretical Computer Science

      4.5

      (1.4k 条评论)

      Advanced · Specialization · 3-6 Months

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      University of Illinois at Urbana-Champaign

      Data Mining

      您将获得的技能: Machine Learning, Data Analysis, Data Mining, Natural Language Processing, Machine Learning Algorithms, Data Science, Data Visualization, Probability & Statistics, Interactive Data Visualization, Python Programming, Statistical Programming, Bayesian Statistics, C Programming Language Family, Computer Programming, Algorithms, Applied Machine Learning, Bioinformatics, Business Psychology, Calculus, Computer Graphics, Data Management, Data Structures, Entrepreneurship, General Statistics, Geovisualization, Mathematics, Network Analysis, Project Management, Spatial Data Analysis, Statistical Analysis, Strategy and Operations, Theoretical Computer Science

      4.5

      (2.8k 条评论)

      Intermediate · Specialization · 3-6 Months

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      Coursera Project Network

      Transfer Learning for NLP with TensorFlow Hub

      您将获得的技能: Applied Machine Learning, Computer Programming, Databases, Deep Learning, Machine Learning, Natural Language Processing, Python Programming, Statistical Programming, Tensorflow

      4.8

      (150 条评论)

      Intermediate · Guided Project · Less Than 2 Hours

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      DeepLearning.AI

      Natural Language Processing with Attention Models

      您将获得的技能: Deep Learning, Machine Learning, Artificial Neural Networks, Natural Language Processing, Python Programming, Statistical Programming, Computer Programming, Human Computer Interaction, Machine Learning Algorithms, User Experience

      4.3

      (834 条评论)

      Intermediate · Course · 1-4 Weeks

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      University of Michigan

      PostgreSQL for Everybody

      您将获得的技能: Databases, SQL, Computer Programming, Data Management, Statistical Programming, Machine Learning, PostgreSQL, Cloud Computing, Database Application, Database Design, Theoretical Computer Science, NoSQL, Data Model, Cloud Applications, Javascript, Natural Language Processing, Python Programming, Software Architecture, Software Engineering, Web Development, Computational Logic, Data Structures, Mathematical Theory & Analysis, Mathematics, Programming Principles

      4.7

      (830 条评论)

      Intermediate · Specialization · 3-6 Months

    与 nlp 相关的搜索

    nlp modelos y algoritmos
    nlp: twitter sentiment analysis
    nlp system architecture and dev-ops
    deploy bridgerton nlp sms text generator
    deploy an nlp text generator: bart simpson chalkboard gag
    transfer learning for nlp with tensorflow hub
    building a unique nlp project: 1984 book vs 1984 album
    البرمجة اللغوية العصبية | nlp
    1234…29

    总之,这是我们最受欢迎的 nlp 门课程中的 10 门

    • Natural Language Processing: DeepLearning.AI
    • Machine Learning: DeepLearning.AI
    • Deep Learning: DeepLearning.AI
    • Natural Language Processing in TensorFlow: DeepLearning.AI
    • Fine Tune BERT for Text Classification with TensorFlow: Coursera Project Network
    • Natural Language Processing with Classification and Vector Spaces: DeepLearning.AI
    • NLP: Twitter Sentiment Analysis: Coursera Project Network
    • Advanced Machine Learning on Google Cloud: Google Cloud
    • Data Mining: University of Illinois at Urbana-Champaign
    • Transfer Learning for NLP with TensorFlow Hub: Coursera Project Network

    您可以在 Software Development 中学到的技能

    程序设计语言 (34)
    Google (25)
    计算机程序 (21)
    软件测试 (21)
    网络 (19)
    Google 云端平台 (18)
    应用程序接口 (17)
    数据数据结构 (16)
    解决问题 (14)
    面向对象程序设计 (13)
    Kubernetes (10)
    列表和标签 (10)

    关于 Nlp 的常见问题

    • Natural language processing, or NLP, is the field of artificial intelligence (AI) focused on enabling computers to understand and use human language. By drawing on insights from linguistics and cutting edge computer science, NLP is playing an increasingly important role in helping computers understand people - and, conversely, in helping humans better navigate our increasingly digital world.

      For example, NLP is essential to programming digital assistants that respond accurately to voice commands, such as Alexa or Google Home. It also enables the creation of chatbots capable of addressing common customer service inquiries. Beyond customer-facing tools, NLP is also used for sentiment analysis applications used by businesses to assess social media responses to their brand, or services capable of automatically creating clearly-written summaries of text or datasets.

      Like other areas of AI and deep learning, NLP relies on machine learning (ML) algorithms organized in neural network architectures. Because neural networks mimic the structure of the human brain itself, these approaches are particularly well suited for natural language processing. And, as with other AI/ML applications, work in NLP is most commonly done in TensorFlow or Python programming.

      Natural language processing is one of the trending job skills in Coursera's 2020 Global Skills Index (GSI). Download the 2020 edition of the GSI report.‎

    • It’s an exciting time to work in natural language processing, as more and more organizations are exploring ways to use chatbots, digital assistants, and other NLP applications. This trend has been further accelerated by the Covid-19 epidemic, as the transition away from physical help desks and customer service departments has led companies to try new modes of interacting with customers. Thus, a familiarity with NLP approaches can be useful to software developers, data scientists, and other professionals in tech.

      Professionals wishing to leverage their expertise in natural language processing to develop new approaches in this field may pursue a master’s degree or even a doctorate in computer science. In NLP and other areas, computer research scientists are in high demand; according to the Bureau of Labor Statistics, they earn a median annual salary of $122,840 per year, and jobs in this field are expected to grow much faster than average over the next decade.‎

    • Certainly. Coursera offers a wealth of courses and Specializations in computer science, data science, and artificial intelligence, including courses specifically focused on NLP applications. These courses are offered by top-ranked institutions such as deeplearning.ai, the University of Michigan, and the National Research University Higher School of Economics. You can also learn about NLP with hands-on Guided Projects from Coursera, which help you build new skills with tutorials presented by experienced instructors.‎

    • The skills or experience you may need to have before starting to learn about natural language processing (NLP) can include understanding the basics of linguistics, programming, and statistical analysis. You may also want to have the ability to understand the basic concepts of artificial intelligence. Also, you may need to have some familiarity with the basics of linear algebra, probability theory, machine learning setup, and deep neural networks. The ability to understand linguistics means you may already know the meaning of semantics and symbolism in language. Having a basic understanding of programming and statistical analysis may be required because NLP is used to help humans interact with all kinds of computers and devices. In addition, you have experience in industries, such as medicine, law, or finance and banking, you may already have some skills needed to learn NLP because artificial intelligence, or the algorithms used to understand and manipulate human language, is already being used for tools such as medical records, legal documents, and financial insights.‎

    • The kind of person best suited to learn NLP is interested in language and words. People who like to understand the subtle and ambiguous ways that words and sentences convey meaning to a human enjoy learning about NLP. Someone interested in how devices use artificial intelligence to make decisions for humans may be well suited to learn NLP. A person who is comfortable living in the world of automated language and personal assistants (such as Siri and Alexa) may find learning NLP worthwhile too.‎

    • Learning NLP may be right for you if you're passionate about the future of artificial intelligence. NLP may be beneficial for you to learn if you plan to work as a software developer in the field of artificial intelligence that requires complex programming skills, applications, and systems such as machine translation of sentences and building chatbots, for example. NLP may be beneficial for you to learn if you need to understand algorithms, such as Naïve Bayes Classifier, which is a common classification algorithm that makes fast machine predictions. Studying NLP may also be right for you if you are a software developer who needs to understand how to build NLP systems using TensorFlow, a popular open-source framework for machine learning.‎

    此常见问题解答内容仅供参考。建议学生多做研究,确保所追求的课程和其他证书符合他们的个人、专业和财务目标。
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