Deep Learning and Natural Language Processing
Deep learning (or Deep Neural Networks) is an important subset of machine learning and artificial intelligence which is based on artificial neural networks (ANN) to mimic the human brain. Like biological neurons, which are present in the human brain, it also contains a vast number of artificial neurons, which are used to identify and store information. Deep learning covers multiple techniques such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), including Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU), Auto-Encoder (AE), Deep Belief Network (DBN), Generative Adversarial Network (GAN), and Deep Reinforcement Learning (DRL). In recent years, deep learning has great success and obtains state-of-the-art in a variety of application domains including computer vision, medical imaging, bioinformatics, cybersecurity, speech recognition, machine translation, natural language processing, etc. Among those, Natural language processing (NLP) is one of the most important technologies of the information age. Manipulating and understanding complex human language is also a crucial part of artificial intelligence. Many NLP tasks such as language modeling, sentiment analysis, language translation, spam detection, topic categorization, image description, video captioning, summarization and many more have obtained very high performance by deep learning approaches.