Deep learning has revolutionized the field of natural language processing and led to many state-of-the-art results. This course introduces students to neural network models and training algorithms frequently used in natural language processing. At the end of this course, learners will be able to explain and implement feedforward networks, recurrent neural networks, and transformers. They will also have an understanding of transfer learning and the inner workings of large language models. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder

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📚Books(3)

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Speech and Language Processing

Speech and Language Processing - A book resource

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Natural Language Processing with Python

Natural Language Processing with Python - A book resource

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Deep Learning for Natural Language Processing

Deep Learning for Natural Language Processing - A book resource

intermediate🇬🇧

🌐Websites(6)

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Papers with Code - NLP

Papers, code, and leaderboards for NLP tasks

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NLP Progress

State-of-the-art results on NLP benchmarks

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Hugging Face NLP Course

Free interactive course on modern NLP

beginner🇬🇧

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nlp.stanford.edu

Stanford NLP is the official site of Stanford's Natural Language Processing Group, featuring their research, projects, and publications, along with NLP software and resources. It offers tools like CoreNLP and Stanza, datasets, tutorials, and information about courses and seminars.

intermediate🇬🇧

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huggingface.co

Hugging Face is an open‑source AI platform centered on NLP, hosting a large Model Hub of pre‑trained transformers, plus the Datasets library and community Spaces. It provides model cards, documentation, tutorials, and tools to train, evaluate, and deploy NLP models.

intermediate🇬🇧

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towardsdatascience.com

Towards Data Science is a popular online publication offering accessible tutorials, explainers, and practical guides on data science, machine learning, and NLP. It features articles with code samples and notebooks that cover concepts, techniques, and real-world NLP applications.

intermediate🇬🇧

Frequently Asked Questions

What are the best free resources to learn Natural Language Processing?

Dantes has curated 7 resources for Natural Language Processing, including 1 videos, 3 courses, 3 websites. All resources are hand-picked for quality — no algorithmic filler. Browse the full list above to find the format that works best for you.

Is Natural Language Processing hard to learn?

Natural Language Processing is approachable at the beginner level — there are resources here specifically for those starting from scratch. As you progress, intermediate and advanced material is also available to take your skills further.

What types of Natural Language Processing learning resources are available on Dantes?

For Natural Language Processing, Dantes has curated 1 videos, 3 courses, 3 websites. Each resource type serves a different learning style: videos and YouTube for visual learners, books for depth, courses for structured progression, and websites for quick reference.

How does Dantes select Natural Language Processing resources?

Dantes is an algorithm-free learning directory. Resources are hand-curated based on quality, accuracy, and usefulness — not engagement metrics or paid placements. The goal is to surface the best learning material for Natural Language Processing, whether it's a free YouTube series, a classic textbook, or an open courseware from a top university.

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