SpaCy Training
Level
IntermediateDuration
16h / 2 daysDate
Individually arrangedPrice
Individually arrangedSpaCy Training
The SpaCy training is an intensive two-day course focused on the practical use of the spaCy library for Natural Language Processing (NLP) in Python. The program is designed so that 80% of the time is dedicated to workshops and 20% to theory. Participants will gain skills in text analysis, building NLP models, and automating language processing using spaCy, working with real-world examples and use cases.
What You Will Learn
- Install and configure spaCy for NLP
- Perform basic text operations: tokenization, lemmatization, stopword removal
- Carry out syntactic analysis, named entity recognition (NER), and sentiment analysis
- Build and train text classification models with spaCy
Requirements
- Basic knowledge of Python programming
- Basic understanding of data processing
- Ability to work with Python libraries
Who is this training for?
Programmers and data engineers wanting to expand into NLP
Data scientists and analysts interested in text processing and analysis
IT specialists looking to use spaCy for language processing automation
Training Program
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Day 1: Introduction to NLP and spaCy Basics
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Fundamentals of Natural Language Processing (NLP)
- Introduction to NLP: definitions and applications
- Overview of NLP tools and techniques
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Introduction to spaCy
- Installation and configuration
- Overview of spaCy modules and core functions
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Basic Operations in spaCy
- Text tokenization (words and sentences)
- Lemmatization and stopword removal
- Morphological analysis
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Text Analysis with spaCy
- Implementing basic text processing operations
- Analyzing simple text datasets
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Day 2: Advanced Techniques and Practical Applications
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Syntactic and Semantic Analysis
- Part-of-speech (POS) tagging
- Dependency parsing and parse trees
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Named Entity Recognition (NER) and Sentiment Analysis
- Techniques for recognizing named entities
- Methods for sentiment analysis in text
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Building NLP Models with spaCy
- Creating and training text classification models
- Using spaCy corpora to build custom NLP models