Solving NLP Problems with BERT, N-gram, Embedding, LSTM, GRU, Self-Attention, Transformer 🔥🔥🔥🔥

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The video was published under the license of the Creative Commons Attribution license (reuse allowed) and is reposted for educational purposes.
Source: https://youtu.be/MtP-UAyVuZY

In this talk Álvaro will introduce the concept of language models, and review some of the state of the art approaches to building such models (BERT, GPT-2 and XLNet), delving into the network architecture and training strategies used in them. Then he will move on to show how these pre-trained language models can be fine-tuned to small datasets to produce high quality results in downstream NLP tasks, by making use of the open-source PyTorch-Transformers library (https://github.com/huggingface/transformers). This library is built on top of the PyTorch deep learning framework, and allows loading pre-trained language models and fine-tuning them easily. This talk will be focused on the theoretical grounds of these methods and on his practical experience in applying them.

Видео Solving NLP Problems with BERT, N-gram, Embedding, LSTM, GRU, Self-Attention, Transformer 🔥🔥🔥🔥 канала AIP - Pursuing SoTA AI for everyone