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GitHub - oxford-cs-deepnlp-2017/lectures: Oxford Deep NLP 2017 course

#artificialintelligence

This repository contains the lecture slides and course description for the Deep Natural Language Processing course offered in Hilary Term 2017 at the University of Oxford. This is an advanced course on natural language processing. Automatically processing natural language inputs and producing language outputs is a key component of Artificial General Intelligence. The ambiguities and noise inherent in human communication render traditional symbolic AI techniques ineffective for representing and analysing language data. This is an applied course focussing on recent advances in analysing and generating speech and text using recurrent neural networks.


Deep Learning for NLP at Oxford with Deep Mind 2017 - YouTube

@machinelearnbot

This playlist contains the lecture videos for the Deep Natural Language Processing course offered in Hilary Term 2017 at the University of Oxford. This is an advanced course on natural language processing. Automatically processing natural language inputs and producing language outputs is a key component of Artificial General Intelligence. The ambiguities and noise inherent in human communication render traditional symbolic AI techniques ineffective for representing and analysing language data. Recently statistical techniques based on neural networks have achieved a number of remarkable successes in natural language processing leading to a great deal of commercial and academic interest in the field This is an applied course focusing on recent advances in analysing and generating speech and text using recurrent neural networks.


Deep Learning for Natural Language Processing

#artificialintelligence

This is an advanced course on natural language processing. Automatically processing natural language inputs and producing language outputs is a key component of Artificial General Intelligence. The ambiguities and noise inherent in human communication render traditional symbolic AI techniques ineffective for representing and analysing language data. This will be an applied course focussing on recent advances in analysing and generating speech and text using recurrent neural networks. We will introduce the mathematical definitions of the relevant machine learning models and derive their associated optimisation algorithms.


Neural networks and deep learning with Microsoft Azure GPU

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The rise of neural networks and deep learning is correlated with increased computational power introduced by general purpose GPUs. The reason is that the optimisation problems being solved to train a complex statistical model, are demanding and the computational resources available are crucial to the final solution. Using a conventional CPU, one could spend weeks of waiting for a simple neural network to be trained. This problem is amplified when one is trying to spawn multiple experiments to select optimal parameters of a model. Having computational resources such as a high-end GPU is an important aspect when one begins to experiment with deep learning models as this allows a rapid gain in practical experience.


10 Free Top Notch Natural Language Processing Courses - KDnuggets

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Autumn is as good a season to learn natural language processing as any other, and why not do so with quality, free online courses? This is a collection of just such free, quality online NLP courses, from such esteemed institutions of learning as Stanford, Oxford, University of Washington, and UC Berkeley. There are also offerings from independent sources like Yandex Data School, and even a short practical course on spaCy by one of its creators and co-founder of the company which steers its development. So whether you are looking for theoretical or practical, or are a beginner or an advanced learner, the content included herein won't fail on living up to the promise of being 10 free top notch natural language processing courses. So dig in and learn NLP today.