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Neural machine translation (NMT), Text summarization, Question Answering, Chatbot
You will learn the newest state-of-the-art Natural language processing (NLP) Deep-learning approaches.
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Neural machine translation (NMT)
A family of machine learning approaches used for natural language processing.
A technique that mimics cognitive attention.
An approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modelling entire sentences in a single integrated model.
An algorithm for training the weights of recurrent neural networks (RNNs).
An algorithm for evaluating the quality of text which has been machine-translated from one natural language to another.
A heuristic search algorithm that explores a graph by expanding the most promising node in a limited set.
A deep learning model that adopts the mechanism of self-attention, differentially weighting the significance of each part of the input data.
An autoregressive language model that uses deep learning to produce human-like text.
A transformer-based machine learning technique for natural language processing (NLP) pre-training developed by Google.
An algorithmic technique that hashes similar input items into the same "buckets" with high probability.
A variant of ResNets where each layer's activations can be reconstructed exactly from the next layer's.
Introduces two techniques to improve the efficiency of Transformers.
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