(强推)2021吴恩达深度学习-NLP序列模型
coursera
Deeplearning.AI今年更新了深度学习第四课CNN(BV1e54y1b7uk)和第五课NLP，光处理成双栏字幕就花了我好久时间。
人工智能技术探讨群：571218304，不定期分享干货与大厂研讨会（抽奖+兼职），点赞关注一起进步。
视频选集
（1/37）
1.1_why-sequence-models
03:01
1.2_notation
09:16
1.3_recurrent-neural-network-model
16:32
1.4_backpropagation-through-time
06:12
1.5_different-types-of-rnns
09:34
1.6_language-model-and-sequence-generation
12:02
1.7_sampling-novel-sequences
08:39
1.8_vanishing-gradients-with-rnns
06:29
1.9_gated-recurrent-unit-gru
17:07
1.10_long-short-term-memory-lstm
09:54
1.11_bidirectional-rnn
08:20
1.12_deep-rnns
05:17
2.1_word-representation
10:08
2.2_using-word-embeddings
09:23
2.3_properties-of-word-embeddings
11:55
2.4_embedding-matrix
05:58
2.5_learning-word-embeddings
10:09
2.6_word2vec
12:48
2.7_negative-sampling
11:54
2.8_glove-word-vectors
11:09
2.9_sentiment-classification
07:38
2.10_debiasing-word-embeddings
11:09
3.1_basic-models
06:12
3.2_picking-the-most-likely-sentence
08:57
3.3_beam-search
11:55
3.4_refinements-to-beam-search
11:01
3.5_error-analysis-in-beam-search
09:44
3.6_bleu-score-optional
16:27
3.7_attention-model-intuition
09:42
3.8_attention-model
12:23
3.9_speech-recognition
08:54
3.10_trigger-word-detection
04:32
4.1_transformer-network-intuition
05:30
4.2_self-attention
11:44
4.3_multi-head-attention
08:21
4.4_transformer-network
13:11
4.5_conclusion-and-thank-you
02:45
顶部