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.
Ce cours fait partie de la Spécialisation Deep Learning
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Spécialisation Deep Learningdeeplearning.aiÀ propos de ce cours
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Cours 5 sur 5 dans le
Niveau intermédiaire
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Approx. 42 heures pour terminer
Anglais
Sous-titres : Anglais, Coréen, Arabe
Compétences que vous acquerrez
- Natural Language Processing
- Long Short Term Memory (LSTM)
- Gated Recurrent Unit (GRU)
- Recurrent Neural Network
- Attention Models
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 5 sur 5 dans le
Niveau intermédiaire
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Approx. 42 heures pour terminer
Anglais
Sous-titres : Anglais, Coréen, Arabe
Offert par
deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.
Programme de cours : ce que vous apprendrez dans ce cours
14 heures pour terminer
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 heures pour terminer
12 vidéos (Total 112 min), 4 lectures, 6 quiz
9 heures pour terminer
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 heures pour terminer
10 vidéos (Total 99 min), 1 lecture, 4 quiz
10 heures pour terminer
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 heures pour terminer
10 vidéos (Total 98 min), 3 lectures, 4 quiz
9 heures pour terminer
Transformer Network
9 heures pour terminer
5 vidéos (Total 42 min), 4 lectures, 3 quiz
Avis
- 5 stars83,61 %
- 4 stars13,05 %
- 3 stars2,57 %
- 2 stars0,48 %
- 1 star0,28 %
Meilleurs avis pour MODÈLES DE SÉQUENCES
par SS1 janv. 2020
Learnt a lot about new concepts in RNN and LSTM. Really wanted to learn about these models. This course helped a lot. Everything was new and so fascinating. Loved this course and our teach Andrew NG.
par AM4 juil. 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.
par GS26 avr. 2019
So many possibilities will be presented in front of you after this course. The only limit is the boundary of my imagination and creativity, that is how I feel now upon the completion of this course.
par SS14 déc. 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!
À propos du Spécialisation Deep Learning
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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