Technologies / Artificial Intelligence

Summarizing text using Python

A specialized training course on automatic text summarization techniques in Python. Participants will learn a variety of methods for extracting and generating summaries, from statistical approaches to advanced neural models. Hands-on workshops form the main part of the class, allowing immediate application of the learned techniques in real projects.

Issues

Techniques for extracting key information
Generative models in text summarization
Language transformers and models
Metrics for evaluating the quality of abstracts
Text preprocessing
Managing the length of abstracts
Control of the style of the generated texts
Multilingual summary
Optimization of generative models
Processing long documents
Maintaining consistency of abstracts
Adapting to the specifics of the field

Benefits

The participant will learn to design and implement automatic text summarization systems
He or she will gain a working knowledge of various summary generation techniques, from statistical methods to deep learning
Will develop the ability to evaluate the quality of generated summaries and optimize them
Will learn the latest trends in the field of automatic text summarization
Will be able to adapt models to specific needs and text types
Will gain the ability to integrate summarization systems into existing applications

Who is this training for?

Python programmers working with text data

Data analysts specializing in NLP

Document processing specialists

AI engineers involved in automation

Developers of content management systems

Researchers involved in text analysis

Content marketing specialists

Prerequisites

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

Training program

Extraction vs. abstraction
Metrics for evaluating the quality of abstracts
Preparation of text data

Sentence ranking algorithms

Clustering techniques
Selection of key passages

Sequence-to-sequence models
Transformers in generating abstracts
Fine-tuning language models
Controlling the length and style of abstracts

Building a processing pipeline
Evaluation of the quality of abstracts
Performance optimization
Integration with applications

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

What are the prerequisites for this training?

For Summarizing text using Python we recommend: Knowledge of the Python language at an intermediate level; Basic knowledge of word processing; Understand the basics of machine learning.

What is the format and duration of this training?

The training lasts 2 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: Python programmers working with text data; Data analysts specializing in NLP; Document processing specialists.