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  1. ML-NLP ML-NLP Public

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    此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。

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    HanLP作者的新书《自然语言处理入门》详细笔记!业界良心之作,书中不是枯燥无味的公式罗列,而是用白话阐述的通俗易懂的算法模型。从基本概念出发,逐步介绍中文分词、词性标注、命名实体识别、信息抽取、文本聚类、文本分类、句法分析这几个热门问题的算法原理与工程实现。

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  3. CodingInterviews2-ByPython CodingInterviews2-ByPython Public

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  4. Model_Log Model_Log Public

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    Model Log 是一款基于 Python3 的轻量级机器学习(Machine Learning)、深度学习(Deep Learning)模型训练评估指标可视化工具,可以记录模型训练过程当中的超参数、Loss、Accuracy、Precision、F1值等,并以曲线图的形式进行展现对比,轻松三步即可实现。

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