Sequence Models (Complete Course) скачать в хорошем качестве

Sequence Models (Complete Course)

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. -------- TIME STAMP -------- 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 Debaising word Embeddings SEQUENC MODELS & ATTENTION MECHANISM 3:34:20 BAsic Models 3:40:31 Picking the Most likely Sentense 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! ⭐ Important Notes ⭐ ⌨️ This course is created in collaboration with Deeplearning.ai (Andrew NG) 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 HuggingFace 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. #NaturalLanguageProcessing, #LongShortTermMemory(LSTM), #AttentionModels, #GatedRecurrentUnit(GRU), #RecurrentNeuralNetwork, #neuralnetwork, #Deeplearning, #Machinelearning,