Notes:
Deep learning is a type of machine learning that involves using artificial neural networks to learn from data and make predictions or decisions. In contrast to traditional machine learning algorithms, which are often designed to work with a specific type of data and require manual feature engineering, deep learning algorithms can automatically learn and extract features from raw data.
One of the key applications of deep learning is in natural language processing, which is the use of computer algorithms to understand and generate human language. Dialog systems, which are also known as conversational agents or chatbots, use natural language processing to understand and respond to user input in a conversational manner. Deep learning algorithms can be used to train dialog systems to understand and generate human language, allowing them to engage in more natural and human-like conversations with users. This is especially useful in applications such as customer service, where a chatbot can be trained to understand and respond to a wide range of customer inquiries and requests.
Wikipedia:
References:
See also:
100 Best GitHub: Deep Learning | 100 Best Natural Language Deep Learning Videos | Skipgrams, Deep Learning & Question Answering 2017
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- Deep Learning Tutorial part 13 Transfer learning
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- NIPS2017 Tutorial—Geometric deep learning on graphs and manifolds
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- Synthetic Gradients Tutorial – How to Speed Up Deep Learning Training
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