Natural Language Processing

3 courses

Token Classification in NLP using spaCy

Delve into token classification in NLP with this focused learning path. This course centers on using spaCy for token classification, from setting up an NLP pipeline to advanced classification model fine-tuning. Upon completion, you'll be adept in utilizing spaCy for token classification in NLP.

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This learning path includes:

3 courses with bite-sized lessons and practices

13 engaging lessons in text and video formats

56 hands-on practices

One-on-one guidance from Cosmo, our AI tutor

Verified skills you'll gain

INTERMEDIATE

Linguistics and Semantics

INTERMEDIATE

Text Data Collection and Preparation

DEVELOPING

Machine Learning Modeling for NLP

Tools you'll use

NLTK

Python

spaCy

Trusted by learners working at top companies

5 lessons

25 practices

Building an NLP Pipeline with spaCy for Token Classification

Kickstart your journey into token classification by setting up an efficient NLP pipeline, learning about tokenization, POS tagging, and lemmatization with spaCy.

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5 lessons

21 practices

Linguistics for Token Classification in spaCy

Delve deeper into fully enhancing Token Classification by understanding linguistic and semantic aspects of Natural Language Processing. Gain grasp of language morphology and recognize entity types using spaCy.

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3 lessons

10 practices

Practical Applications of spaCy for Real-Life Tasks

Understanding theory and basic tools of spaCy is of paramount importance, but applying them to real-life tasks is what drives value. The course focuses on four case studies that involve practical applications of spaCy to solve real-world problems.

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Meet Cosmo: The smartest AI guide in the universe

Our built-in AI guide and tutor, Cosmo, prompts you with challenges that are built just for you and unblocks you when you get stuck.

Whether you’re leveling up or just starting out, find your next step here.