Natural language processing (NLP) has become a hot topic in the field of artificial intelligence, whether it is intelligent assistants, search engines, social media analysis, emotional computing, can not be separated from natural language processing technology support. Through systematic teaching and practice, this course aims to help students master the core technology of NLP, improve their data processing and text analysis skills, and lay a solid foundation for their future career development. This course is mainly aimed at school students and sociologists, and scholars who want to master artificial intelligence technology can join this course. 1. Course structure: Basic knowledge: To enable students to have a comprehensive understanding of natural language processing technology. Pre-technology: to make programming preparations for subsequent learning. Basic algorithm: To prepare algorithms for completing different natural language processing tasks. Processing word vectors: enabling machines to understand and process text information. Processing tasks: including text classification and text generation, through practical projects to enable students to master the practical application of natural language technology. Install the Python programming language and commonly used NLP libraries (such as NLTK, spaCy, gensim, etc.). An integrated development environment (IDE) such as PyCharm or Jupyter Notebook is recommended to improve programming efficiency.
Rules for recognition of learning outcomes
