![]() ![]() Learn about Siamese networks, a special type of neural network made of two identical networks that are eventually merged, then build your own Siamese network that identifies question duplicates in a dataset from Quora. Then build your own Named Entity Recognition system using an LSTM and data from Kaggle. It covers the theoretical descriptions and. Learn how long short-term memory units (LSTMs) solve the vanishing gradient problem and how Named Entity Recognition systems quickly extract essential information from text. This project contains an overview of recent trends in deep learning based natural language processing (NLP). Week 3: LSTMs and Named Entity Recognition (NER) Then build your own next-word generator using a simple RNN on Shakespeare text data. Learn about the limitations of traditional language models and see how RNNs and GRUs use sequential data for text prediction. ![]() Week 2: Recurrent Neural Networks for Language Modeling This 11-video course explores the concept of deep learning and implementation of deep learning-based frameworks for natural language processing (NLP) and audio data analysis. Learn about neural networks for deep learning, then build a sophisticated tweet classifier that places tweets into positive or negative sentiment categories using a deep neural network. What is Natural Language Processing Main NLP use cases Natural language processing or NLP is a branch of Artificial Intelligence that gives machines the ability to understand natural human speech. Applied Deep Learning: Unsupervised Data. Week 1: Neural Network for Sentiment Analysis
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