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Mastering spaCy · LearnSpace
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courseraПрограммирование

Mastering spaCy

Курс от Packt
Средний≈ 12 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course teaches advanced techniques in Natural Language Processing (NLP) using spaCy and spaCy-LLM. You’ll learn how to integrate LLMs into your NLP workflows, creating custom components and models. Designed for both beginners and experienced developers, this course provides hands-on examples to help you master spaCy’s core functionalities. It equips you to apply transformer models and fine-tune them for specialized NLP tasks. What sets this course apart is its practical approach. You’ll learn to build end-to-end NLP workflows and gain skills in deploying production-ready solutions, making it ideal for real-world applications. This course is perfect for NLP engineers, machine learning developers, and software engineers. A basic understanding of Python and NLP concepts is recommended for the best experience.

Навыки, которые вы освоите

Natural Language ProcessingModel TrainingSoftware InstallationLarge Language ModelingModel DeploymentWorkflow ManagementModel EvaluationTransfer LearningAutomationData ProcessingText MiningArtificial Intelligence and Machine Learning (AI/ML)Application DeploymentPython ProgrammingApplication Programming Interface (API)LLM Application

Программа курса

11 модулей · 66 учебных материалов

01Getting Started with spaCy6 материалов

Lesson 1

Introduction - Overview VideoВидеоGetting Started with spaCy - Overview VideoВидеоIntroductionЧтениеInstalling spaCyЧтение

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Packt - Course Instructors

Преподаватель курса

Mastering spaCy
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 12 ч

11 модулей

Язык: Английский

Часть программы вашего университета
Introduction to spaCy and NLP FundamentalsЗадание
Discussion: Choosing the Right NLP ToolОбсуждение
02Core Operations with spaCy6 материалов

Lesson 1

Core Operations with spaCy - Overview VideoВидеоIntroductionЧтениеSentence SegmentationЧтениеTokenЧтениеMore spaCy Token FeaturesЧтениеCore Operations with spaCyЗадание
03Extracting Linguistic Features5 материалов

Lesson 1

Extracting Linguistic Features - Overview VideoВидеоIntroductionЧтениеVerb Tense and Aspect in NLU ApplicationsЧтениеIntroducing NERЧтениеLinguistic Feature AnalysisЗадание
04Mastering Rule-Based Matching8 материалов

Lesson 1

Mastering Rule-Based Matching - Overview VideoВидеоIntroductionЧтениеExtended Syntax SupportЧтениеRegex-like OperatorsЧтениеPractice: Analyze Trade-offs in Rule-Based MatchingDIALOGUERegex SupportЧтениеCombining spaCy Models and MatchersЧтениеMastering Rule-Based Matching in spaCyЗадание
05Extracting Semantic Representations with spaCy Pipelines6 материалов

Lesson 1

Extracting Semantic Representations with spaCy Pipelines - Overview VideoВидеоIntroductionЧтениеAdding the SpanRuler Component to Our Processing PipelineЧтениеSentence ObjectЧтениеCreating a Pipeline Component Using Extension AttributesЧтениеExploring spaCy Pipeline Customization and Semantic ExtractionЗадание
06Utilizing spaCy with Transformers9 материалов

Lesson 1

Utilizing spaCy with Transformers - Overview VideoВидеоIntroductionЧтениеFrom LSTMs to TransformersЧтениеText Classification with spaCyЧтениеReflect: Choosing Your NLP Model SetupDIALOGUEPreparing the Data for spaCy Trainable ComponentsЧтениеUsing Hugging Face Transformers in SpaCyЧтениеBERT and RoBERTaЧтениеTransformer Models and spaCy FundamentalsЗадание
07Enhancing NLP Tasks Using LLMs with Spacy-LLM6 материалов

Lesson 1

Enhancing NLP Tasks Using LLMs with Spacy-LLM - Overview VideoВидеоIntroductionЧтениеText Summarization with LLMs and Spacy-LLMЧтениеCreating Custom Spacy-LLM TasksЧтениеEnhancing NLP with LLMs in spaCyЗаданиеDiscussion: Building vs. Reusing spaCy-LLM TasksОбсуждение
08Training an NER Component with Your Own Data4 материалов

Lesson 1

Training an NER Component with Your Own Data - Overview VideoВидеоIntroductionЧтениеAnnotating and Preparing DataЧтениеMastering NER Pipeline CustomizationЗадание
09Creating End-to-End spaCy Workflows with Weasel7 материалов

Lesson 1

Creating End-to-End spaCy Workflows with Weasel - Overview VideoВидеоIntroductionЧтениеModifying a Project Template for a Different Use CaseЧтениеPractice: Design a Reproducible NLP WorkflowDIALOGUEUploading and Downloading Project Outputs to Remote StorageЧтениеHow DVC Addresses Common Data Science and ML ChallengesЧтениеManaging NLP Workflows with DVC and WeaselЗадание
10Training an Entity Linker Model with spaCy5 материалов

Lesson 1

Training an Entity Linker Model with spaCy - Overview VideoВидеоIntroductionЧтениеBest Practices for Creating a Good NLP CorpusЧтениеEntity Linking and Knowledge Base IntegrationЗаданиеDiscussion: Building Reliable Entity Linking SystemsОбсуждение
11Integrating spaCy with Third-Party Libraries4 материалов

Lesson 1

Integrating spaCy with Third-Party Libraries - Overview VideoВидеоIntroductionЧтениеBuilding APIs for NLP Models Using FastAPIЧтениеSpaCy and Web Framework IntegrationЗадание