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.
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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. 42 horas para completar
Inglês
Legendas: Inglês, Coreano, Árabe
Habilidades que você terá
- Natural Language Processing
- Long Short Term Memory (LSTM)
- Gated Recurrent Unit (GRU)
- Recurrent Neural Network
- Attention 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. 42 horas para completar
Inglês
Legendas: Inglês, Coreano, 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
10 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.
10 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
- 5 stars83,61%
- 4 stars13,06%
- 3 stars2,55%
- 2 stars0,48%
- 1 star0,28%
Principais avaliações do MODELOS DE SEQUÊNCIA
por WK13 de mar de 2018
I was really happy because I could learn deep learning from Andrew Ng. The lectures were fantastic and amazing.\n\nI was able to catch really important concepts of sequence models.\n\nThanks a lot!
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 AM4 de jul de 2018
Excellent course! This course extensively covers all of the relevant areas of NLP with a strong practical element allowing you to applying Deep Learning for Sequence Models in real-world scenarios.
por SS14 de dez de 2018
Please work on getting the notebooks to work properly. Also very bummed that after canceling my subscription, I won't have access to my homeworks. You guys should give us lifelong access - we paid!
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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