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
Pytorch implementation of Tacotron

Tacotron-pytorch A pytorch implementation of Tacotron: A Fully End-to-End Text-To-Speech Synthesis Model. Requirements Install python 3 Install pytorc

soobin seo 203 Dec 02, 2022
A simple version of DeTR

DeTR-Lite A simple version of DeTR Before you enjoy this DeTR-Lite The purpose of this project is to allow you to learn the basic knowledge of DeTR. P

Jianhua Yang 11 Jun 13, 2022
Generate vector graphics from a textual caption

VectorAscent: Generate vector graphics from a textual description Example "a painting of an evergreen tree" python text_to_painting.py --prompt "a pai

Ajay Jain 97 Dec 15, 2022
A raytrace framework using taichi language

ti-raytrace The code use Taichi programming language Current implement acceleration lvbh disney brdf How to run First config your anaconda workspace,

蕉太狼 73 Dec 11, 2022
Python SDK for working with Voicegain Speech-to-Text

Voicegain Speech-to-Text Python SDK Python SDK for the Voicegain Speech-to-Text API. This API allows for large vocabulary speech-to-text transcription

Voicegain 3 Dec 14, 2022
Easy-to-use CPM for Chinese text generation

CPM 项目描述 CPM(Chinese Pretrained Models)模型是北京智源人工智能研究院和清华大学发布的中文大规模预训练模型。官方发布了三种规模的模型,参数量分别为109M、334M、2.6B,用户需申请与通过审核,方可下载。 由于原项目需要考虑大模型的训练和使用,需要安装较为复杂

382 Jan 07, 2023
Practical Natural Language Processing Tools for Humans is build on the top of Senna Natural Language Processing (NLP)

Practical Natural Language Processing Tools for Humans is build on the top of Senna Natural Language Processing (NLP) predictions: part-of-speech (POS) tags, chunking (CHK), name entity recognition (

jawahar 20 Apr 30, 2022
Chatbot with Pytorch, Python & Nextjs

Installation Instructions Make sure that you have Python 3, gcc, venv, and pip installed. Clone the repository $ git clone https://github.com/sahr

Rohit Sah 0 Dec 11, 2022
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models

Novetta 407 Jan 03, 2023
تولید اسم های رندوم فینگیلیش

karafs کرفس تولید اسم های رندوم فینگیلیش installation ➜ pip install karafs usage دو زبانه ➜ karafs -n 10 توت فرنگی بی ناموس toot farangi-ye bi_namoos

Vaheed NÆINI (9E) 36 Nov 24, 2022
Repository to hold code for the cap-bot varient that is being presented at the SIIC Defence Hackathon 2021.

capbot-siic Repository to hold code for the cap-bot varient that is being presented at the SIIC Defence Hackathon 2021. Problem Inspiration A plethora

Aryan Kargwal 19 Feb 17, 2022
Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models

Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more than just a paraphrasing model.

Prithivida 681 Jan 01, 2023
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
Mapping a variable-length sentence to a fixed-length vector using BERT model

Are you looking for X-as-service? Try the Cloud-Native Neural Search Framework for Any Kind of Data bert-as-service Using BERT model as a sentence enc

Han Xiao 11.1k Jan 01, 2023
German Text-To-Speech Engine using Tacotron and Griffin-Lim

jotts JoTTS is a German text-to-speech engine using tacotron and griffin-lim. The synthesizer model has been trained on my voice using Tacotron1. Due

padmalcom 6 Aug 28, 2022
This is the 25 + 1 year anniversary version of the 1995 Rachford-Rice contest

Rachford-Rice Contest This is the 25 + 1 year anniversary version of the 1995 Rachford-Rice contest. Can you solve the Rachford-Rice problem for all t

13 Sep 20, 2022
构建一个多源(公众号、RSS)、干净、个性化的阅读环境

2C 构建一个多源(公众号、RSS)、干净、个性化的阅读环境 作为一名微信公众号的重度用户,公众号一直被我设为汲取知识的地方。随着使用程度的增加,相信大家或多或少会有一个比较头疼的问题——广告问题。 假设你关注的公众号有十来个,若一个公众号两周接一次广告,理论上你会面临二十多次广告,实际上会更多,运

howie.hu 678 Dec 28, 2022
Original implementation of the pooling method introduced in "Speaker embeddings by modeling channel-wise correlations"

Speaker-Embeddings-Correlation-Pooling This is the original implementation of the pooling method introduced in "Speaker embeddings by modeling channel

Themos Stafylakis 10 Apr 30, 2022
Ελληνικά νέα (Python script) / Greek News Feed (Python script)

Ελληνικά νέα (Python script) / Greek News Feed (Python script) Ελληνικά English Το 2017 είχα υλοποιήσει ένα Python script για να εμφανίζει τα τωρινά ν

Loren Kociko 1 Jun 14, 2022
ConvBERT-Prod

ConvBERT 目录 0. 仓库结构 1. 简介 2. 数据集和复现精度 3. 准备数据与环境 3.1 准备环境 3.2 准备数据 3.3 准备模型 4. 开始使用 4.1 模型训练 4.2 模型评估 4.3 模型预测 5. 模型推理部署 5.1 基于Inference的推理 5.2 基于Serv

yujun 7 Apr 08, 2022