This repository consists of a complete guide on natural language processing (NLP) in Python where we'll learn various techniques for implementing NLP including parsing & text processing and understand how to use NLP for text feature engineering.

Overview

Last Commit Last Commit Stars Badge Forks Badge Size Pull Requests Badge Issues Badge Language MIT License

binder colab

Python_Natural_Language_Processing

This repository contains tutorials on important topics related to Natural Language Processing (NPL).

No. Name
01 01_Tokenization_NLP
02 02_Stemming_Lemmatization
03 03_StopWords
04 04_Vocabulary_and_Matching
05 05_POS_Basics
06 06_Named_Entity_Recognition
07 07_Sentence_Segmentation
08 08_Stemming
09 09_BagofWords_N_Gram
10 10_TF_IFD

These are read-only versions. However you can Run ▶ all the codes online by clicking here ➞ binder 020_Road_Detection

Frequently asked questions

How can I thank you for writing and sharing this tutorial? 🌷

You can Star Badge and Fork Badge Starring and Forking is free for you, but it tells me and other people that it was helpful and you like this tutorial.

Go here if you aren't here already and click ➞ ✰ Star and ⵖ Fork button in the top right corner. You will be asked to create a GitHub account if you don't already have one.


How can I read this tutorial without an Internet connection? GIF

  1. Go here and click the big green ➞ Code button in the top right of the page, then click ➞ Download ZIP.

    Download ZIP

  2. Extract the ZIP and open it. Unfortunately I don't have any more specific instructions because how exactly this is done depends on which operating system you run.

  3. Launch ipython notebook from the folder which contains the notebooks. Open each one of them

    Kernel > Restart & Clear Output

This will clear all the outputs and now you can understand each statement and learn interactively.

If you have git and you know how to use it, you can also clone the repository instead of downloading a zip and extracting it. An advantage with doing it this way is that you don't need to download the whole tutorial again to get the latest version of it, all you need to do is to pull with git and run ipython notebook again.


Authors ✍️

I'm Dr. Milaan Parmar and I have written this tutorial. If you think you can add/correct/edit and enhance this tutorial you are most welcome 🙏

See github's contributors page for details.

If you have trouble with this tutorial please tell me about it by Create an issue on GitHub PNG and I'll make this tutorial better. This is probably the best choice if you had trouble following the tutorial, and something in it should be explained better. You will be asked to create a GitHub account if you don't already have one.

If you like this tutorial, please give it a star.


Licence 📜

You may use this tutorial freely at your own risk. See LICENSE.

Owner
Milaan Parmar / Милан пармар / _米兰 帕尔马
💼👨‍🏫 Researcher • Python | MATLAB | R • Build🤯 → Test🤞 → Debug✔️ “Change Is the Only Constant in Life" ➶
Milaan Parmar / Милан пармар / _米兰 帕尔马
Code for "Finetuning Pretrained Transformers into Variational Autoencoders"

transformers-into-vaes Code for Finetuning Pretrained Transformers into Variational Autoencoders (our submission to NLP Insights Workshop 2021). Gathe

Seongmin Park 22 Nov 26, 2022
DaCy: The State of the Art Danish NLP pipeline using SpaCy

DaCy: A SpaCy NLP Pipeline for Danish DaCy is a Danish preprocessing pipeline trained in SpaCy. At the time of writing it has achieved State-of-the-Ar

Kenneth Enevoldsen 71 Jan 06, 2023
This repository contains examples of Task-Informed Meta-Learning

Task-Informed Meta-Learning This repository contains examples of Task-Informed Meta-Learning (paper). We consider two tasks: Crop Type Classification

10 Dec 19, 2022
[EMNLP 2021] LM-Critic: Language Models for Unsupervised Grammatical Error Correction

LM-Critic: Language Models for Unsupervised Grammatical Error Correction This repo provides the source code & data of our paper: LM-Critic: Language M

Michihiro Yasunaga 98 Nov 24, 2022
NLP command-line assistant powered by OpenAI

NLP command-line assistant powered by OpenAI

Axel 16 Dec 09, 2022
Fidibo.com comments Sentiment Analyser

Fidibo.com comments Sentiment Analyser Introduction This project first asynchronously grab Fidibo.com books comment data using grabber.py and then sav

Iman Kermani 3 Apr 15, 2022
A CRM department in a local bank works on classify their lost customers with their past datas. So they want predict with these method that average loss balance and passive duration for future.

Rule-Based-Classification-in-a-Banking-Case. A CRM department in a local bank works on classify their lost customers with their past datas. So they wa

ÖMER YILDIZ 4 Mar 20, 2022
BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

303 Dec 17, 2022
This code is the implementation of Text Emotion Recognition (TER) with linguistic features

APSIPA-TER This code is the implementation of Text Emotion Recognition (TER) with linguistic features. The network model is BERT with a pretrained mod

kenro515 1 Feb 08, 2022
Transformers and related deep network architectures are summarized and implemented here.

Transformers: from NLP to CV This is a practical introduction to Transformers from Natural Language Processing (NLP) to Computer Vision (CV) Introduct

Ibrahim Sobh 138 Dec 27, 2022
Honor's thesis project analyzing whether the GPT-2 model can more effectively generate free-verse or structured poetry.

gpt2-poetry The following code is for my senior honor's thesis project, under the guidance of Dr. Keith Holyoak at the University of California, Los A

Ashley Kim 2 Jan 09, 2022
PyTorch implementation of Tacotron speech synthesis model.

tacotron_pytorch PyTorch implementation of Tacotron speech synthesis model. Inspired from keithito/tacotron. Currently not as much good speech quality

Ryuichi Yamamoto 279 Dec 09, 2022
BookNLP, a natural language processing pipeline for books

BookNLP BookNLP is a natural language processing pipeline that scales to books and other long documents (in English), including: Part-of-speech taggin

654 Jan 02, 2023
Collection of useful (to me) python scripts for interacting with napari

Napari scripts A collection of napari related tools in various state of disrepair/functionality. Browse_LIF_widget.py This module can be imported, for

5 Aug 15, 2022
Contract Understanding Atticus Dataset

Contract Understanding Atticus Dataset This repository contains code for the Contract Understanding Atticus Dataset (CUAD), a dataset for legal contra

The Atticus Project 273 Dec 17, 2022
2021 AI CUP Competition on Traditional Chinese Scene Text Recognition - Intermediate Contest

繁體中文場景文字辨識 程式碼說明 組別:這就是我 成員:蔣明憲 唐碩謙 黃玥菱 林冠霆 蕭靖騰 目錄 環境套件 安裝方式 資料夾布局 前處理-製作偵測訓練註解檔 前處理-製作分類訓練樣本 part.py : 從 json 裁切出分類訓練樣本 Class.py : 將切出來的樣本按照文字分類到各資料夾

HuanyueTW 3 Jan 14, 2022
Use Tensorflow2.7.0 Build OpenAI'GPT-2

TF2_GPT-2 Use Tensorflow2.7.0 Build OpenAI'GPT-2 使用最新tensorflow2.7.0构建openai官方的GPT-2 NLP模型 优点 使用无监督技术 拥有大量词汇量 可实现续写(堪比“xx梦续写”) 实现对话后续将应用于FloatTech的Bot

Watermelon 9 Sep 13, 2022
1 Jun 28, 2022
Research Code for NeurIPS 2020 Spotlight paper "Large-Scale Adversarial Training for Vision-and-Language Representation Learning": UNITER adversarial training part

VILLA: Vision-and-Language Adversarial Training This is the official repository of VILLA (NeurIPS 2020 Spotlight). This repository currently supports

Zhe Gan 109 Dec 31, 2022
DeepSpeech - Easy-to-use Speech Toolkit including SOTA ASR pipeline, influential TTS with text frontend and End-to-End Speech Simultaneous Translation.

(简体中文|English) Quick Start | Documents | Models List PaddleSpeech is an open-source toolkit on PaddlePaddle platform for a variety of critical tasks i

5.6k Jan 03, 2023