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Technologies / Artificial Intelligence

NLP with spaCy library in Python

Specialized training in the use of the spaCy library in natural language processing tasks. The program focuses on the practical application of advanced spaCy functions in NLP projects. Participants learn techniques for efficient text processing and implementation of language solutions through hands-on workshops. The classes are conducted in the form of intensive programming labs.

Issues

  • Architecture and components of spaCy

  • Language models and pipelines

  • Real-time text processing

  • Recognition of naming units

  • Syntactic and semantic analysis

  • Vector representations of text

  • Training your own components

  • Expanding spaCy functionality

  • Performance optimization

  • Multilingual processing

  • Integration with other libraries

  • Best implementation practices

Benefits

  • Practical knowledge in using the spaCy library in NLP projects
  • Will develop the ability to implement advanced text processing functions
  • Will learn to customize and extend the library's capabilities to meet specific project needs
  • Will learn techniques for optimizing and scaling spaCy-based solutions
  • Will be able to effectively use language models in various NLP tasks
  • Will gain the ability to integrate spaCy with other tools and libraries

Who is this training for?

Python programmers working with text data
NLP analysts using spaCs
ML engineers implementing language solutions
Developers of word processing systems
Information extraction specialists
Researchers involved in the analysis of language
AI solution architects

Prerequisites

  • Knowledge of the Python language at an intermediate level
  • Basic knowledge of natural language processing
  • Experience in working with NLP libraries
  • Understand the basics of machine learning

Training program

01

Library architecture and capabilities

  • Language models and pipelines
  • Tokenization and segmentation
02

Syntactic analysis

  • Advanced spaCy features
  • Recognition of naming units
  • Analysis of syntactic relationships
03

Text classification

  • Vectorization and embedding
  • Customizing spaCy models
  • Training your own components
  • Expanding functionality
04

Create your own rules

  • Performance optimization
  • Integration and implementation
  • Processing large collections of text
  • Integration with other libraries
05

Scaling up solutions

  • Good manufacturing practices

Delivery Methods

Online

  • Convenience of participating from anywhere
  • Interactive live sessions with trainer
  • Materials available for 30 days
  • No travel costs

On-site

  • Direct contact with trainer and group
  • Intensive hands-on workshops
  • Networking with other participants
  • Full focus on learning

Frequently asked questions

Who is the NLP with spaCy library in Python training for?

This training is designed for professionals looking to develop skills in nlp with spacy library in python. Required level: advanced.

How long is the NLP with spaCy library in Python training?

The training lasts 2. Available in online or on-site format.

Will I receive a certificate?

Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.

Can this training be conducted for a closed group?

Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.

Bożena Machowska-Worek
Bożena Machowska-Worek Opiekun szkolenia

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Funding Options

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Up to 80%

Development Services Database

Up to 80% funding for SMEs from EU funds

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Up to 100%

National Training Fund

Up to 100% funding for employers

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We train teams at Poland's largest companies

ING Bank - EITT client
mBank - EITT client
PKO Bank Polski - EITT client
PZU - EITT client
Allianz - EITT client
T-Mobile - EITT client
KGHM - EITT client
PGE - EITT client
IKEA - EITT client
InPost - EITT client
Leroy Merlin - EITT client
ZUS - EITT client

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Contact us - we'll prepare an offer tailored to your organization's needs.

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