1. 介绍
由吴恩达主持的NLP课程。网址
上面链接打不开，可在B站看，网址
计划：先翻译全视频，其次按照课程简要归纳概括，最后自己写总结博客。
时间安排：2020-7-6~2020-9-30
2. 课程内容
Course 1: Natural Language Processing with Classification and Vector Spaces
课程1：使用分类和词向量的自然语言处理
Week 1: Sentiment Analysis with Logistic Regression
情感分析和逻辑回归
12 个视频 （总计 37 分钟）, 3 个阅读材料, 1 个测验
Welcome to the NLP Specialization (4分钟)
Supervised ML & Sentiment Analysis (2分钟)
Vocabulary & Feature Extraction (2分钟)
Negative and Positive Frequencies (2分钟)
Feature Extraction with Frequencies (2分钟)
Preprocessing (3分钟)
Putting it All Together (2分钟)
Logistic Regression Overview (3分钟)
Logistic Regression: Training (1分钟)
Logistic Regression: Testing (4分钟)
Logistic Regression: Cost Function (5分钟)
3 个阅读材料
Connect with your mentors and fellow learners on Slack! (10分钟)
Acknowledgement - Ken Church (10分钟)
How to refresh your workspace (10分钟)
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Week 2: Naïve Bayes
朴素贝叶斯
11 个视频 （总计 40 分钟）
Probability and Bayes’ Rule (2分钟)
Bayes’ Rule (3分钟)
Naïve Bayes Introduction (5分钟)
Laplacian Smoothing (2分钟)
Log Likelihood, Part (15分钟)
Log Likelihood, Part (21分钟)
Training Naïve Bayes (3分钟)
Testing Naïve Bayes (4分钟)
Applications of Naïve Bayes (3分钟)
Naïve Bayes Assumptions (3分钟)
Error Analysis (3分钟)
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Week 3: Word Embeddings
词嵌入
8 个视频 （总计 26 分钟）
Vector Space Models (2分钟)
Word by Word and Word by Doc. (4分钟)
Euclidean Distance (3分钟)
Cosine Similarity: Intuition (2分钟)
Cosine Similarity (3分钟)
Manipulating Words in Vector Spaces (3分钟)
Visualization and PCA (3分钟)
PCA Algorithm (3分钟)
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Week 4: Word Translation
词翻译
8 个视频 （总计 29 分钟）, 2 个阅读材料, 1 个测验
Overview (1分钟)
Transforming word vectors (6分钟)
K-nearest neighbors (3分钟)
Hash tables and hash functions (3分钟)
Locality sensitive hashing (5分钟)
Multiple Planes (3分钟)
Approximate nearest neighbors (3分钟)
Searching documents (1分钟)
2 个阅读材料
Acknowledgements (10分钟)
Bibliography (10分钟)
Course 2: Natural Language Processing with Probabilistic Models
课程2：使用概率模型的自然语言处理
Week 1: Autocorrect and Dynamic Programming
动纠错和动态编程
9个视频(总计27分钟)，1个阅读材料，1个测验
Intro to Course 2 (1分钟)
Overview (1分钟)
Autocorrect (2分钟)
Building the model (3分钟)
Minimum edit distance (2分钟)
Minimum edit distance algorithm (5分钟)
Minimum edit distance algorithm II (3分钟)
Minimum edit distance algorithm III (2分钟)
1个阅读材料
How to Refresh your Workspace (10分钟)
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Week 2: Part of Speech Tagging and Hidden Markov Models
部分语音标签和隐式马尔科夫模型
11个视频(总计38分钟)
Part of speech Tagging (2分钟)
Markov Chains (3分钟)
Markov Chains and POS Tags (4分钟)
Hidden Markov Models (3分钟)
Calculating Probabilities (3分钟)
Populating the Emission Matrix (2分钟)
The Viterbi Algorithm (3分钟)
Viterbi: Initialization (2分钟)
Viterbi: Forward Pass (2分钟)
Viterbi: Backward Pass (5分钟)
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Week 3: Autocomplete and Language Models
自动完成和语言模型
9个视频(总计50分钟)
N-Grams: Overview (3分钟)
N-grams and Probabilities (7分钟)
Sequence Probabilities (5分钟)
Starting and Ending Sentences (8分钟)
The N-gram Language Model (6分钟)
Language Model Evaluation (6分钟)
Out of Vocabulary Word (4分钟)
Smoothing (6分钟)
Week Summary (1分钟)
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Week 4: Word embeddings with neural networks
用神经网络做词嵌入
20个视频(总计65分钟)
Overview (2分钟)
Basic Word Representations (3分钟)
Word Embeddings (3分钟)
How to Create Word Embeddings (3分钟)
Word Embedding Methods (3分钟)
Continuous Bag-of-Words Model (3分钟)
Cleaning and Tokenization (4分钟)
Sliding Window of Words into Vectors (2分钟)
Architecture of the CBOW Model: Dimensions (3分钟)
Architecture of the CBOW Model: Dimensions 2 (2分钟)
Architecture of the CBOW Model: Activation Functions (4分钟)
Training a CBOW Model: Cost Function (4分钟)
Training a CBOW Model: Forward Propagation (3分钟)
Training a CBOW Model: Backprogageation and Gradient Descent (4分钟)
Extracting Word Embedding Vectors (2分钟)
Evaluating Word Embeddings: Intrinsic Evaluation (3分钟)
Evaluating Word Embeddings: Extrinsic Evaluation (2分钟)
Conclusion (2分钟)
Course 3: Natural Language Processing with Sequence Models
课程3：使用序列模型的自然语言处理
Week 1: 6 个视频 （总计 25 分钟）
C3W1L01 (3分钟)
C3W1L02 (3分钟)
C3W1L03 (4分钟)
C3W1L04 (4分钟)
C3W1L05 (5分钟)
C3W1L06 (3分钟)
Course 4: Natural Language Processing with Attention Models
课程4： 使用注意力机制模型的自然语言处理
Week 1: Neural Machine Translation
神经机器翻译
8 个视频 （总计 35 分钟）
1 (2分钟)
2 (4分钟)
3 (6分钟)
4 (3分钟)
5 (7分钟)
6 (2分钟)
7 (2分钟)
8 (5分钟)
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Week 2: Text Summarization
文本摘要
7 个视频 （总计 32 分钟）
1 (3分钟)
2 (6分钟)
3 (5分钟)
4 (3分钟)
5 (4分钟)
6 (4分钟)
7 (3分钟)