LSTM Neural Network for Textual Ngrams

Cognitive neuroscience is the study of how the human brain functions on tasks like decision making, language, perception and reasoning. Deep learning is a class of machine learning algorithms that use neural networks. They are designed to model the responses of neurons in the human brain. Learning can be supervised or unsupervised. Ngram token models are used extensively in language prediction. Ngrams are probabilistic models that are used in predicting the next word or token. They are a statistical model of word sequences or tokens and are called Language Models or Lms. Ngrams are essential in creating language prediction models. We are exploring a broader sandbox ecosystems enabling for AI. Specifically, around Deep learning applications on unstructured content form on the web.

认知神经科学 (Cognitive neuroscience) 是研究人类大脑如何完成决策、语言、感知与推理等任务的学科。深度学习 (Deep learning) 是一类使用神经网络 (neural networks) 的机器学习算法，旨在模拟人类大脑神经元的响应活动。学习范式可分为监督学习 (supervised learning) 与无监督学习 (unsupervised learning) 两类。Ngram Token模型 (Ngram token models) 被广泛应用于语言预测任务中。Ngram是一类用于预测下一个单词或Token (token) 的概率模型，其本质是针对单词序列或Token的统计模型，亦可称为语言模型 (Language Models，简称LMs)，是构建语言预测模型的核心要素。我们正在探索一个可支持人工智能的更广泛的沙盒生态系统，具体而言，该生态系统聚焦于深度学习在网页端非结构化内容上的应用。