Sequence Models Complete Course
Don't Forget To Subscribe, Like & Share Subscribe, Like & Share
If you want me to upload some courses please tell me in the comments. Don't Forget To Subscribe, Like & Share
If you want me to upload some courses please tell me in the comments.
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.
RECURRENT NEURAL NETWORKS
0:00:00 Why Sequence Models
0:03:00 Notation
0:12:15:Recurrent Neural Models
0:28:46 Backpropagation Through Time
0:34:57 Different Types of RNNs
0:44:31 Language Models and Sequence Generation
0:56:32 Sampling Novel Sequences
1:05:11 Vanishing Gradients with RNNs
NATURAL LANGUAGE PROCESSING & WORD EMBEDDINGS
1:11:39 Gated Recurrent Unit (GRU)
1:28:46 Long Short Term Memory (LSTM)
1:38:40 Bidirectional RNN
1:46:59 Deep RNNs
1:52:15 Word Representation
2:02:23 Using Word Embeddings
2:11:45 Properties of Word Embeddings
2:23:39 Embedding Matrix
2:29:37 Learning Word Embeddings
2:39:46 Word2Vec
2:52:33 Negative Sampling
3:04:26 Glove word Vectors
3:15:35 Sentiment Classification
3:23:12 Debiasing word Embeddings
SEQUENC MODELS & ATTENTION MECHANISM
3:34:20 Basic Models
3:40:31 Picking the Most likely Sentence
3:49:27 Beam Search
4:01:22 Refinements to Beam Search
4:12:22 Error Analysis in Beam Search
4:22:06 Bleu Score (Optional)
4:38:32 Attention Model Intuition
4:48:14 Attention Model
5:00:37 Speech Recognition
5:09:30 Trigger Word Detection
TRANSFORMER NETWORK
5:14:02 Transformer Network Intuition
5:19:31 Self-Attention
5:31:14 Multi-Head Attention
5:39:35 Transformer Network
5:52:45 Conclusion and Thank you!
By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use Hugging Face tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering.
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. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career.
⭐ Important Notes ⭐
⌨️ The creator of this course is Deeplearning.ai (Andrew Ng)
Note: If you have any copyright issue with the content used in our channel or you find something that belongs to you, before you claim it to Youtube, SEND US A MESSAGE and the respective content will be DELETED right away. Thanks for understanding.
#NaturalLanguageProcessing,
#LongShortTermMemory(LSTM),
#AttentionModels,
#GatedRecurrentUnit(GRU),
#RecurrentNeuralNetwork,
#coursera,
#neuralnetwork,
#Deeplearning,
#Machinelearning,
#sequence models,
#why sequence models,
#sequence modeling,
#sequence models andrew ng,
#sequence to sequence models,
#sequence,
#deeplearning.ai sequence models course,
#sequence to sequence,
#language model and sequence generation,
#sequence model,
#sequences,
#sequence to sequence model,
#data sequence,uml sequence diagram,
#sampling novel sequences,models,
#sequence diagram,
#sequence diagrams,
#sequence generation,
#how to draw sequence diagram,
#uml sequesnce diagram
If you want me to upload some courses please tell me in the comments. Don't Forget To Subscribe, Like & Share
If you want me to upload some courses please tell me in the comments.
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.
RECURRENT NEURAL NETWORKS
0:00:00 Why Sequence Models
0:03:00 Notation
0:12:15:Recurrent Neural Models
0:28:46 Backpropagation Through Time
0:34:57 Different Types of RNNs
0:44:31 Language Models and Sequence Generation
0:56:32 Sampling Novel Sequences
1:05:11 Vanishing Gradients with RNNs
NATURAL LANGUAGE PROCESSING & WORD EMBEDDINGS
1:11:39 Gated Recurrent Unit (GRU)
1:28:46 Long Short Term Memory (LSTM)
1:38:40 Bidirectional RNN
1:46:59 Deep RNNs
1:52:15 Word Representation
2:02:23 Using Word Embeddings
2:11:45 Properties of Word Embeddings
2:23:39 Embedding Matrix
2:29:37 Learning Word Embeddings
2:39:46 Word2Vec
2:52:33 Negative Sampling
3:04:26 Glove word Vectors
3:15:35 Sentiment Classification
3:23:12 Debiasing word Embeddings
SEQUENC MODELS & ATTENTION MECHANISM
3:34:20 Basic Models
3:40:31 Picking the Most likely Sentence
3:49:27 Beam Search
4:01:22 Refinements to Beam Search
4:12:22 Error Analysis in Beam Search
4:22:06 Bleu Score (Optional)
4:38:32 Attention Model Intuition
4:48:14 Attention Model
5:00:37 Speech Recognition
5:09:30 Trigger Word Detection
TRANSFORMER NETWORK
5:14:02 Transformer Network Intuition
5:19:31 Self-Attention
5:31:14 Multi-Head Attention
5:39:35 Transformer Network
5:52:45 Conclusion and Thank you!
By the end, you will be able to build and train Recurrent Neural Networks (RNNs) and commonly-used variants such as GRUs and LSTMs; apply RNNs to Character-level Language Modeling; gain experience with natural language processing and Word Embeddings; and use Hugging Face tokenizers and transformer models to solve different NLP tasks such as NER and Question Answering.
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. It provides a pathway for you to take the definitive step in the world of AI by helping you gain the knowledge and skills to level up your career.
⭐ Important Notes ⭐
⌨️ The creator of this course is Deeplearning.ai (Andrew Ng)
Note: If you have any copyright issue with the content used in our channel or you find something that belongs to you, before you claim it to Youtube, SEND US A MESSAGE and the respective content will be DELETED right away. Thanks for understanding.
#NaturalLanguageProcessing,
#LongShortTermMemory(LSTM),
#AttentionModels,
#GatedRecurrentUnit(GRU),
#RecurrentNeuralNetwork,
#coursera,
#neuralnetwork,
#Deeplearning,
#Machinelearning,
#sequence models,
#why sequence models,
#sequence modeling,
#sequence models andrew ng,
#sequence to sequence models,
#sequence,
#deeplearning.ai sequence models course,
#sequence to sequence,
#language model and sequence generation,
#sequence model,
#sequences,
#sequence to sequence model,
#data sequence,uml sequence diagram,
#sampling novel sequences,models,
#sequence diagram,
#sequence diagrams,
#sequence generation,
#how to draw sequence diagram,
#uml sequesnce diagram
همه توضیحات ...