Learning NLPIR semantic intelligence teaching and research platform should be opened like this

　　NLPIR Big Data Semantic Intelligence Teaching and Research Platform is a comprehensive teaching and research platform for big data semantic intelligence analysis major. The platform is centered on natural language understanding, combined with the BIT team's years of scientific research and front-line teaching experience, and is committed to improving the level of students' big data and artificial intelligence teaching and training, scientific research and engineering practice in a scientific and rigorous way.
　　The NLPIR Big Data Semantic Intelligent Teaching and Research Platform has a complete and rich teaching system, including course materials, video teaching, practical training platform, experimental verification and project cases.
　　The NLPIR Big Data Semantic Intelligence Teaching and Research Platform has rich teaching content, mainly focusing on the three core areas of big data, artificial intelligence and natural language understanding. The core content includes the following aspects:
　　1) The scientific concept of big data: the definition of big data, The origin of scientific development; how to treat big data scientifically? How to grasp big data, and expound the scientific big data view from three levels of "knowledge", "microscopic" and "xiaoyi".
　　2) Big data technology platform and architecture: cloud computing technology and open source platform construction; Hadoop, Spark and other data architectures, computing paradigms and application practices; TensorFlow deep learning platform.
　　3) Machine learning and common data mining: common machine learning algorithms: Bayes, SVM, deep neural network, etc.; common data mining techniques: association rule mining, classification, clustering, singularity analysis; deep learning: CNN, RNN, LSTM, Attention model, seq2seq model.
　　4) Big data semantic precision search: the contradiction between general search engine and big data vertical business; the basic technology of big data precision search: fast incremental inverted index, structured and unstructured data fusion, big data sorting algorithm, semantic association , automatic caching and optimization mechanism; big data precise search syntax: proximity search, compound search, emotional search, precise search;
　　5) Unstructured big data semantic mining
　　Semantic understanding foundation: ICTCLAS and Chinese word segmentation; content key semantic automatic indexing and word cloud automatic generation; big data clustering; big data classification and information filtering; big data deduplication and automatic summarization; sentiment analysis and sentiment calculation; bad information intelligence Filter.
　　6) Automatic construction and application of big data of knowledge graph: knowledge graph concept; automatic discovery of knowledge points; knowledge big data generation based on bootstrapping;
　　7) NLPIR intelligent semantic platform: NLPIR intelligent semantic analysis online cloud service; NLPIR Parser semantics Analysis platform training; NLPIR intelligent semantic secondary development interface and tutorial.
　　8) Analysis and overview of big data application cases: power grid big data application cases; new media communication innovation and headline application; unstructured big data mining.