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所在平台: Udemy |
课程主页: https://www.udemy.com/course/applied-ml-build-nlp-text-embeddings-using-python/
课程评论：没有评论
**Coursera 课程摘要：应用机器学习：使用 Python 构建 NLP 文本嵌入** 本课程将引导您深入了解自然语言处理（NLP）这一人工智能和机器学习的关键领域。NLP 专注于处理非结构化文本数据，无论是人类还是机器生成。 **您将学到：** * NLP 在人工智能和机器学习整体图景中的位置。 * 文本嵌入（Embeddings）的概念、目的和重要性。嵌入是将文本数据转化为数值格式的关键技术，是进行更高级 NLP 任务（如机器翻译、聊天机器人开发等）的基础。 * NLP 数据处理的丰富性和挑战性，以及如何通过机器学习模型来利用这些数据。 **课程特色：** * 提供扎实的 NLP 基础概念。 * 包含两个实践性编码练习（提供 Jupyter Notebook），让您亲身体验文本嵌入的应用和价值。 本课程旨在激发您对 NLP 领域的兴趣，并为您进一步探索该领域打下坚实的基础。
Natural Language Processing (NLP) is a subfield of Artificial Intelligence and Machine Learning where we work with unstructured text data - human or machine generated. If you are new to AI and ML space and would like to know where exactly NLP fits in the bigger picture, I would like to suggest the course "Applied ML: The Big Picture"But once you've arrived here with the interest in NLP, I'd like to say you've taken the right step of knowing more about this interesting and challenging field. The language we speak is rich in information across several dimensions and to even realize these dimensions is a research exercise in itself. For this reason, NLP data is one of the most exciting data one can work with, while developing ML models.Embeddings are just techniques that attempt to decipher some of these dimensions and put them into numerical format. It's the first and most important step before getting into advanced NLP algorithms and tasks such as machine translation, chatbot development etc.This course provides the learner the foundational concepts along with two coding exercises, with attached jupyter notebooks, to provide a practical experience on the purpose and usefulness of text embeddings. Hopefully this inspires and prepares the learner to explore more topics in the interesting field of NLP.
