This course is an introduction to sequence models and their applications, including an overview of sequence model architectures and how to handle inputs of variable length.
Este curso forma parte de Programa especializado: Advanced Machine Learning on Google Cloud
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Acerca de este Curso
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Fechas límite flexibles
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Certificado para compartir
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Nivel avanzado
Aprox. 13 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel avanzado
Aprox. 13 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
ofrecido por
Google Cloud
We help millions of organizations empower their employees, serve their customers, and build what’s next for their businesses with innovative technology created in—and for—the cloud. Our products are engineered for security, reliability, and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping customers apply our technologies to create success.
Programa - Qué aprenderás en este curso
18 minutos para completar
Course introduction
This module addresses the reasons to learn NLP from Google and provides an overview of the course structure and goals.
18 minutos para completar
2 videos (Total 8 minutos), 1 lectura
3 horas para completar
NLP on Google Cloud
This module introduces the NLP architecture on Google Cloud. It explores the NLP history, the NLP APIs such as the Dialogflow API, and the NLP solutions such as Contact Center AI and Document AI.
3 horas para completar
9 videos (Total 39 minutos), 1 lectura, 2 cuestionarios
3 horas para completar
NLP with Vertex AI
This module explores AutoML and custom training, which are the two options to develop an NLP project with Vertex AI. Additionally, the module introduces an end-to-end NLP workflow and provides a hands-on lab to apply the workflow to solve a task of text classification with AutoML.
3 horas para completar
8 videos (Total 23 minutos), 1 lectura, 2 cuestionarios
2 horas para completar
Text representatation
This module describes the process to prepare text data in NLP and introduces the major categories of text representation techniques.
2 horas para completar
8 videos (Total 36 minutos), 1 lectura, 2 cuestionarios
3 horas para completar
NLP models
This module describes different NLP models including ANN, DNN, RNN, LSTM, and GRU. It also introduces the benefits and disadvantages of each model.
3 horas para completar
9 videos (Total 48 minutos), 1 lectura, 2 cuestionarios
Reseñas
- 5 stars63,23 %
- 4 stars22,68 %
- 3 stars8,19 %
- 2 stars2,94 %
- 1 star2,94 %
Principales reseñas sobre NATURAL LANGUAGE PROCESSING ON GOOGLE CLOUD
por DD20 de ene. de 2020
Felt somewhat advanced learning, which made tough to complete intime
por JW10 de nov. de 2018
Excellent course for those who know RNN. Knowledge is refreshed and techniques are consolidated. More details about Google ecosystem is introduced.
por HK30 de nov. de 2018
Very informative, very much useful to my ongoing work on NLP.
por AJ7 de jun. de 2021
The lack of synchronization between the videos and labs is extreme in this course, but the lectures are excellent and the subject area covered is very broad.
Acerca de Programa especializado: Advanced Machine Learning on Google Cloud
This 5-course specialization focuses on advanced machine learning topics using Google Cloud Platform where you will get hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs. This specialization picks up where “Machine Learning on GCP” left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text. It ends with a course on building recommendation systems. Topics introduced in earlier courses are referenced in later courses, so it is recommended that you take the courses in exactly this order.
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