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UCx: Text Analytics 2: Visualizing Natural Language Processing

Extend your knowledge of the core techniques of computational linguistics by working through case-studies and visualizing their results.

6 semanas
3–6 horas por semana
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Sobre este curso

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__ _ Visualizing Natural Language Processing _ is the second course in the Text Analytics with Python professional certificate (or you can study it as a stand-alone course). Natural language processing (NLP) is only useful when its results are meaningful to humans. This second course continues by looking at how to make sense of our results using real-world visualizations.

How can we understand the incredible amount of knowledge that has been stored as text data? This course is a practical and scientific introduction to text analytics. That means you’ll learn how it works and why it works at the same time.

On the practical side, you’ll learn how to visualize and interpret the output of text analytics. You’ll learn how to create visualizations ranging from word clouds, heatmaps, and line plots to distribution plots, choropleth maps, and facet grids. You’ll work through real case-studies using jupyter notebooks and to visualize the results of machine learning in Python using packages like pandas, matplotlib, and seaborn.

On the scientific side, you’ll learn what it means to understand language computationally. How do word embeddings and topic models relate to human cognition? Artificial intelligence and humans don’t view language in the same way. You’ll see how both deep learning and human beings interact with the meaning that is encoded in language.

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  • Idioma: English
  • Transcripción de video: English
  • Habilidades asociadas:Word Embedding, Choropleth Map, Topic Modeling, Pandas (Python Package), Matplotlib, Text Mining, Machine Learning, Computational Linguistics, Deep Learning, Artificial Intelligence, Python (Programming Language), Jupyter, Natural Language Processing

Lo que aprenderás

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  1. Practice using document similarity and topic models to work with large data sets.
  2. Visualize and interpret text analytics, including statistical significance testing.
  3. Assess the scientific and ethical foundations of new applications for text analysis

Plan de estudios

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Module 1. Text Similarity:

Learn how to use machine learning to find out which words and documents have similar meanings.

Module 2. Visualizing Text Analytics:

Learn how to explain a model using visualization and significance testing.

Module 3. Applying Text Analytics to New Fields:

Learn how to apply computational linguistics to new problems and new data sets.

¿Quién puede hacer este curso?

Lamentablemente, las personas residentes en uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.

Este curso es parte del programa Text Analytics with Python Professional Certificate

Más información 
Instrucción por expertos
2 cursos de capacitación
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3 meses
3 - 6 horas semanales

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