In the fifth course of the Deep Learning Specialization, you will become familiar with sequence models and their exciting applications such as speech recognition, music synthesis, chatbots, machine translation, natural language processing (NLP), and more.
Este curso faz parte do Programa de cursos integrados Aprendizagem profunda
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Programa de cursos integrados Aprendizagem profundadeeplearning.aiInformações sobre o curso
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Prazos flexíveis
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Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
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Curso 5 de 5 no
Nível intermediário
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Aprox. 41 horas para completar
Inglês
Legendas: Inglês, Árabe
Habilidades que você terá
Natural Language ProcessingLong Short Term Memory (LSTM)Gated Recurrent Unit (GRU)Recurrent Neural NetworkAttention Models
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 5 de 5 no
Nível intermediário
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Aprox. 41 horas para completar
Inglês
Legendas: Inglês, Árabe
oferecido por
deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.
Programa - O que você aprenderá com este curso
14 horas para concluir
Recurrent Neural Networks
Discover recurrent neural networks, a type of model that performs extremely well on temporal data, and several of its variants, including LSTMs, GRUs and Bidirectional RNNs,
14 horas para concluir
12 vídeos (Total 112 mín.), 4 leituras, 6 testes
9 horas para concluir
Natural Language Processing & Word Embeddings
Natural language processing with deep learning is a powerful combination. Using word vector representations and embedding layers, train recurrent neural networks with outstanding performance across a wide variety of applications, including sentiment analysis, named entity recognition and neural machine translation.
9 horas para concluir
10 vídeos (Total 99 mín.), 1 leitura, 4 testes
9 horas para concluir
Sequence Models & Attention Mechanism
Augment your sequence models using an attention mechanism, an algorithm that helps your model decide where to focus its attention given a sequence of inputs. Then, explore speech recognition and how to deal with audio data.
9 horas para concluir
10 vídeos (Total 98 mín.), 3 leituras, 4 testes
9 horas para concluir
Transformer Network
9 horas para concluir
5 vídeos (Total 42 mín.), 4 leituras, 3 testes
Avaliações
Principais avaliações do SEQUENCE MODELS
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.
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 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 JR25 de Mai de 2019
I am so grateful that Andrew and the team provided such good course, I learn so much from this course, I am so excited that see the wake word detection model actually work in the programming exercise
Sobre Programa de cursos integrados Aprendizagem profunda
The Deep Learning Specialization is a foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology.
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