文件名称：python-tutorial-notebooks：适用于NLP，ML，AI的Jupyter Notebooks Python教程
文件大小：4.51MB
文件格式：ZIP
更新时间：2024-02-24 22:33:19
python natural-language-processing deep-learning parsing neural-network
适用于NLP，ML，AI的Python教程 （C）2016-2020年，（ 另请参阅： 。 请参阅各个文档以及代码文件夹中的文件中的许可详细信息。 此文件夹中的文件是我在计算语言学，自然语言处理（NLP），机器学习（ML）和人工智能（AI）中的课程的基于的NLP，ML，Python人工智能教程。 如果您认为此材料有用，请引用作者和资料来源（即以及相关笔记本中引用的所有资料）。 如果您对如何更正笔记本电脑，改进笔记本电脑或添加一些材料和说明有任何建议，请告诉我。 介绍 要在运行此材料，您需要安装Python 3.x和 。 通过使用您可以省去一些麻烦。 使用以下命令克隆项目文件夹：
【文件预览】：
python-tutorial-notebooks-master
----contributors.txt(12B)
----LICENSE(11KB)
----.gitignore(1KB)
----README.md(5KB)
----notebooks()
--------Python Tutorial Smoothing.ipynb(6KB)
--------Matrix Operations for FSA Computing.ipynb(4KB)
--------FrameNet Examples using NLTK.ipynb(957KB)
--------toy_network_batch.png(162KB)
--------Python and Networks.ipynb(12KB)
--------NDFSAMatrixOp.png(5KB)
--------HMM-Emissions.png(11KB)
--------NLTK_Framenet.ipynb(7.54MB)
--------Cython Examples.ipynb(3KB)
--------Tangent-calculus.svg.png(24KB)
--------toy_network_deriv.png(58KB)
--------LinearAlgebra_Determinant_2x2.png(48KB)
--------NLTK_Propbank.ipynb(24KB)
--------Python examples and notes for Machine Learning for Computational Linguistics.ipynb(45KB)
--------eng.fst(22KB)
--------XOR_Network.png(34KB)
--------Backpropagation.ipynb(20KB)
--------Machine Translation in Python 3 with NLTK.ipynb(7KB)
--------Document Classification Tutorial.ipynb(16KB)
--------Linear Algebra - Eigenvalues and Eigenvectors.ipynb(18KB)
--------Corpus Processing.ipynb(2KB)
--------Python Tutorial PoS Tagging.ipynb(37KB)
--------PyDecisionTreesData.txt(892B)
--------data()
--------Polynomialdeg3.svg.png(12KB)
--------Sample_Generation_Word2vec.png(72KB)
--------Word2Vec.ipynb(40KB)
--------Matrix Decomposition Example for Machine Learning for Computational Linguistics.ipynb(5KB)
--------Backpropagation_Tutorial.ipynb(58KB)
--------Python Word Sense Disambiguation.ipynb(19KB)
--------Flair Basics.ipynb(76KB)
--------sigmoid-deriv-2.png(149KB)
--------Lexical Clustering.ipynb(45KB)
--------Python Scikit-Learn for Computational Linguists.ipynb(45KB)
--------Perceptron Learning in Python.ipynb(11KB)
--------HMM2.png(15KB)
--------Non-Deterministic Automaton Computing.ipynb(12KB)
--------Python Parsing with NLTK and Foma.ipynb(14KB)
--------HMM3.png(15KB)
--------irisModel.dat(4KB)
--------Python Decision Trees.ipynb(19KB)
--------Python WordNet using NLTK.ipynb(13KB)
--------Python for Text Similarities.ipynb(7KB)
--------spanish1.cfg(362B)
--------Python Linear Transformations.ipynb(2KB)
--------t-test for comparison of experimental results.ipynb(6KB)
--------Topic Modeling with MALLET.ipynb(7KB)
--------512px-Gradient_descent.svg.png(38KB)
--------Test-notebook for class.ipynb(1KB)
--------Linear Algebra - Matrix Calculus.ipynb(4KB)
--------sigmoid.png(14KB)
--------Recurrent Neural Networks.ipynb(2KB)
--------Neural Network Example with Keras.ipynb(44KB)
--------foma-old.py(19KB)
--------Python Clustering with Scikit-learn.ipynb(10KB)
--------Embedded_Clauses_1.png(48KB)
--------Linear Algebra.ipynb(68KB)
--------600px-Absolute_value.svg.png(6KB)
--------Scikit-Learn-Basic.ipynb(2KB)
--------network1.png(16KB)
--------SigmoidFunction1.png(44KB)
--------Flair Training Sequence Labeling Models.ipynb(175KB)
--------examples()
--------spanish1.fcfg(2KB)
--------sigmoid_prime.png(17KB)
--------Python Feature Extraction for Timbl - Class session.ipynb(70KB)
--------Python NLTK - Texts and Frequencies.ipynb(643KB)
--------Python SVM Classifier Example.ipynb(27KB)
--------WordNet and NLTK.ipynb(25KB)
--------Parsing Natural Language in Python.ipynb(134KB)
--------eng.dot(242KB)
--------Deep Learning Tutorial.ipynb(56KB)
--------Python Language ID.ipynb(147KB)
--------HMM1.png(17KB)
--------PCFG Parsing with NLTK.ipynb(1.21MB)
--------Python Classification and Feature Extraction for Timbl.ipynb(63KB)
--------eng.svg(5.47MB)
--------Combinatory Categorial Grammar Parsing with NLTK.ipynb(17KB)
--------Dependency Grammar in NLTK.ipynb(20KB)
--------Python Tokens and N-grams.ipynb(2.78MB)
--------Bayesian Classifier.ipynb(33KB)
--------Linear Algebra - Creating Vectors from Features.ipynb(3KB)
--------Python Tutorial HMM.ipynb(22KB)
--------Flair Tutorial on Document Classification.ipynb(16KB)
--------grammar.py(2KB)
--------Python Parsing with NLTK.ipynb(34KB)
--------spaCy Tutorial.ipynb(61KB)
--------foma.py(19KB)