課程信息
605,517

第 5 門課程(共 5 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為18 小時

建議:11 hours/week...

英語(English)

字幕:英語(English), 韓語, 中文(簡體)

您將獲得的技能

Recurrent Neural NetworkArtificial Neural NetworkDeep LearningLong Short-Term Memory (ISTM)

第 5 門課程(共 5 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為18 小時

建議:11 hours/week...

英語(English)

字幕:英語(English), 韓語, 中文(簡體)

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 6 小時

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....
12 個視頻 (總計 112 分鐘), 4 個測驗
12 個視頻
Notation9分鐘
Recurrent Neural Network Model16分鐘
Backpropagation through time6分鐘
Different types of RNNs9分鐘
Language model and sequence generation12分鐘
Sampling novel sequences8分鐘
Vanishing gradients with RNNs6分鐘
Gated Recurrent Unit (GRU)17分鐘
Long Short Term Memory (LSTM)9分鐘
Bidirectional RNN8分鐘
Deep RNNs5分鐘
1 個練習
Recurrent Neural Networks20分鐘
2
完成時間為 4 小時

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....
10 個視頻 (總計 102 分鐘), 3 個測驗
10 個視頻
Using word embeddings9分鐘
Properties of word embeddings11分鐘
Embedding matrix5分鐘
Learning word embeddings10分鐘
Word2Vec12分鐘
Negative Sampling11分鐘
GloVe word vectors11分鐘
Sentiment Classification7分鐘
Debiasing word embeddings11分鐘
1 個練習
Natural Language Processing & Word Embeddings20分鐘
3
完成時間為 5 小時

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....
11 個視頻 (總計 103 分鐘), 3 個測驗
11 個視頻
Picking the most likely sentence8分鐘
Beam Search11分鐘
Refinements to Beam Search11分鐘
Error analysis in beam search9分鐘
Bleu Score (optional)16分鐘
Attention Model Intuition9分鐘
Attention Model12分鐘
Speech recognition8分鐘
Trigger Word Detection5分鐘
Conclusion and thank you2分鐘
1 個練習
Sequence models & Attention mechanism20分鐘
4.8
1,548 個審閱Chevron Right

37%

完成這些課程後已開始新的職業生涯

38%

通過此課程獲得實實在在的工作福利

11%

加薪或升職

熱門審閱

創建者 JYOct 30th 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.

創建者 SDSep 28th 2018

Great hands on instruction on how RNNs work and how they are used to solve real problems. It was particularly useful to use Conv1D, Bidirectional and Attention layers into RNNs and see how they work.

講師

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Andrew Ng

CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist,Baidu and founding lead of Google Brain
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Head Teaching Assistant - Kian Katanforoosh

Lecturer of Computer Science at Stanford University, deeplearning.ai, Ecole CentraleSupelec
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Teaching Assistant - Younes Bensouda Mourri

Mathematical & Computational Sciences, Stanford University, deeplearning.ai
Computer Science

關於 deeplearning.ai

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

關於 深度学习 專項課程

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....
深度学习

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