Estudio de Caso de Python - Análisis de Sentimientos

Resumen

This hands-on course equips learners with the practical knowledge and technical skills to develop, implement, and evaluate a sentiment analysis model using Python. Beginning with an introduction to sentiment analysis and its real-world applications, learners will explore and identify appropriate tools including IDEs and essential libraries used in natural language processing (NLP).

As the course progresses, learners will analyze the use of various algorithms suitable for sentiment classification and gain experience in constructing a full analysis pipeline—from data preprocessing and cleaning to model training and evaluation. Each lesson is crafted to reinforce applied learning, enabling participants to demonstrate mastery through building a working sentiment analysis system capable of classifying textual data based on emotional tone.

By the end of the course, learners will be able to:

• Identify key concepts in sentiment analysis. • Select and configure appropriate tools and libraries for text classification. • Implement code for data cleaning, transformation, and feature extraction. • Train and evaluate machine learning models for sentiment classification. • Assess model performance using standard evaluation metrics. This course is ideal for learners with basic Python knowledge who want to delve into NLP and machine learning through a practical, project-based case study.

Programa

• Creación de una Herramienta de Análisis de Sentimientos en Python
Este módulo introduce a los aprendices a los conceptos básicos y herramientas necesarias para construir una aplicación de análisis de sentimientos utilizando Python. Comenzando con una visión conceptual, guía a los aprendices a través de la selección del entorno de desarrollo, la exploración de bibliotecas y algoritmos esenciales, y finalmente, un desglose paso a paso de la implementación del código y procesamiento de datos. El módulo integra prácticas del mundo real, permitiendo a los aprendices aplicar técnicas de aprendizaje automático para analizar y clasificar el sentimiento en datos textuales.

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Impartido por

EDUCBA

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Materias

Computer Science