This course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and many others.
Este curso forma parte de Programa Especializado - Aprendizaje profundo
ofrecido por
Programa Especializado - Aprendizaje profundodeeplearning.aiAcerca de este Curso
1,201,588 vistas recientes
Resultados profesionales del estudiante
39%
comenzó una nueva carrera después de completar estos cursos
40%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
13%
consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 5 de 5 en
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 16 horas para completar
Inglés (English)
Subtítulos: Chino (tradicional), Francés (French), Chino (simplificado), Coreano, Inglés (English), Español (Spanish)
Habilidades que obtendrás
Recurrent Neural NetworkArtificial Neural NetworkDeep LearningLong Short-Term Memory (ISTM)
Resultados profesionales del estudiante
39%
comenzó una nueva carrera después de completar estos cursos
40%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
13%
consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 5 de 5 en
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel intermedio
Aprox. 16 horas para completar
Inglés (English)
Subtítulos: Chino (tradicional), Francés (French), Chino (simplificado), Coreano, Inglés (English), Español (Spanish)
ofrecido por
deeplearning.ai
Founded by Andrew Ng, deeplearning.ai is on a mission to make world-class AI education accessible to people around the globe so that we can all benefit from an AI-powered future.
Programa - Qué aprenderás en este curso
6 horas para completar
Recurrent Neural Networks
Learn about recurrent neural networks. This type of model has been proven to perform extremely well on temporal data. It has several variants including LSTMs, GRUs and Bidirectional RNNs, which you are going to learn about in this section.
6 horas para completar
12 videos (Total 112 minutos), 2 lecturas, 4 cuestionarios
12 videos
Notation9m
Recurrent Neural Network Model16m
Backpropagation through time6m
Different types of RNNs9m
Language model and sequence generation12m
Sampling novel sequences8m
Vanishing gradients with RNNs6m
Gated Recurrent Unit (GRU)17m
Long Short Term Memory (LSTM)9m
Bidirectional RNN8m
Deep RNNs5m
2 lecturas
Gated Recurrent Unit (GRU) *CORRECTION*1m
Long Short Term Memory (LSTM) *CORRECTION*1m
1 ejercicio de práctica
Recurrent Neural Networks30m
4 horas para completar
Natural Language Processing & Word Embeddings
Natural language processing with deep learning is an important combination. Using word vector representations and embedding layers you can train recurrent neural networks with outstanding performances in a wide variety of industries. Examples of applications are sentiment analysis, named entity recognition and machine translation.
4 horas para completar
10 videos (Total 102 minutos), 1 lectura, 3 cuestionarios
10 videos
Using word embeddings9m
Properties of word embeddings11m
Embedding matrix5m
Learning word embeddings10m
Word2Vec12m
Negative Sampling11m
GloVe word vectors11m
Sentiment Classification7m
Debiasing word embeddings11m
1 lectura
GloVe word vectors *CORRECTION*1m
1 ejercicio de práctica
Natural Language Processing & Word Embeddings30m
5 horas para completar
Sequence models & Attention mechanism
Sequence models can be augmented using an attention mechanism. This algorithm will help your model understand where it should focus its attention given a sequence of inputs. This week, you will also learn about speech recognition and how to deal with audio data.
5 horas para completar
11 videos (Total 103 minutos), 4 lecturas, 3 cuestionarios
11 videos
Picking the most likely sentence8m
Beam Search11m
Refinements to Beam Search11m
Error analysis in beam search9m
Bleu Score (optional)16m
Attention Model Intuition9m
Attention Model12m
Speech recognition8m
Trigger Word Detection5m
Conclusion and thank you2m
4 lecturas
Bleu Score *CORRECTION*1m
Corrections10m
Workera's Standardized Tests for AI Skills1m
Instructions if you are unable to open your notebook10m
1 ejercicio de práctica
Sequence models & Attention mechanism30m
Revisiones
Principales revisiones sobre SEQUENCE MODELS
por AC23 de jun. de 2019
Very well produced and explained. In my case, the nature of the Sequence Model makes understanding the concepts and finishing the assignment more challenging than other segments of the specialization.
por PJ3 de abr. de 2019
The previous courses raised the bar and expectations. The assignments for Week 1 and Week 2 were a bit unclear. Lectures for Week 1 and Week 2 can be improved as well. Besides, this is a great course!
por JY29 de oct. de 2018
The lectures covers lots of SOTA deep learning algorithms and the lectures are well-designed and easy to understand. The programming assignment is really good to enhance the understanding of lectures.
por AM30 de jun. de 2019
The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.
Acerca de Programa especializado: Aprendizaje profundo
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.
In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach.
You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.
AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work.
We will help you master Deep Learning, understand how to apply it, and build a career in AI.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Cuál es la política de reembolsos?
Si estás suscrito, obtienes una prueba gratis de 7 días, que podrás cancelar cuando desees sin ningún tipo de penalidad. Una vez transcurrido ese tiempo, no realizamos reembolsos. No obstante, puedes cancelar tu suscripción cuando quieras. Consulta nuestra política completa de reembolsos.
¿Hay ayuda económica disponible?
Sí, Coursera ofrece ayuda económica a los estudiantes que no pueden pagar la tarifa. Solicítala haciendo clic en el enlace de Ayuda económica que está debajo del botón “Inscribirse” a la izquierda. Se te pedirá que completes una solicitud. Recibirás una notificación en caso de que se apruebe. Deberás completar este paso para cada uno de los cursos que forman parte del Programa especializado, incluido el proyecto final. Obtén más información.
¿Recibiré crédito universitario por completar el Curso?
Este Curso no otorga crédito universitario, pero algunas universidades pueden aceptar los Certificados del curso para obtener crédito. Consulta con tu institución para obtener más información. Los Títulos en línea y los Certificados Mastertrack™ de Coursera brindan la oportunidad de obtener créditos universitarios.
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