61 Open source projects that are alternatives of or similar to Pygermanet

Natural Language Processing using NLTK and Spacy

Creating a software for automatic monitoring in online proctoring

📈 Stocks technical analysis code collection and Stocks data platform.

Topic modelling on financial news with Natural Language Processing

📖 [译] Python 自然语言处理 中文第二版

Lectures in Urban Data Science Lab, Seoul

keras project that parses and analyze english resumes

An unsupervised analysis combining topic modeling and clustering to preserve an individuals work history and credentials while tailoring their resume towards a new career field

Ruby port of the NLTK Punkt sentence segmentation algorithm

NLP Cheat Sheet, Python, spacy, LexNPL, NLTK, tokenization, stemming, sentence detection, named entity recognition

My solutions to the projects assigned for the Udacity Computer Vision Nanodegree

Uses topic modeling to identify context between follower relationships of Twitter users

Multi-Class Text Classification for products based on their description with Machine Learning algorithms and Neural Networks (MLP, CNN, Distilbert).

An NLP tool which classifies and summarizes resumes

The hands-on NLTK tutorial for NLP in Python

Machine Learning and NLP: Text Classification using python, scikit-learn and NLTK

Text classification with Reuters-21578 datasets using Gensim Word2Vec and Keras LSTM

Awesome-Text-Classification Projects,Papers,Tutorial .

Generates a quiz for a Wikipedia page using parts of speech and text chunking.

A python chatbot framework with Natural Language Understanding and Artificial Intelligence.

📹 A tool for automatic video creation and uploading on YouTube

This repository provides everything to get started with Python for Text Mining / Natural Language Processing (NLP)

Live Twitter sentiment analysis using Python, Apache Spark Streaming, Kafka, NLTK, SocketIO

Notes and solutions to complement the official NLTK book

An affect generator based on TextBlob and the NRC affect lexicon. Note that lexicon license is for research purposes only.

A SVM model that classifies the reviews as real or fake. Used both the review text and the additional features contained in the data set to build a model that predicted with over 85% accuracy without using any deep learning techniques.

Inhibits commits with bad messages from getting merged

A small NLP SAAS project that summarize a webpage

A company/project name generator for Python. Uses NLTK and diverse techniques derived from existing corporate etymologies and naming agencies for sophisticated word generation and ideation.

A tool to suggest github repositories based on the repositories you have shown interest in.

A factoid based question answering system | Python | Flask | NLP

Russian language support for NLTK's PunktSentenceTokenizer

Extracts key terminology (n-grams) from any large collection of documents (>1000) and forecasts emergence

Python implementation of the Rapid Automatic Keyword Extraction algorithm using NLTK.

NLP with NLTK for Sentiment analysis amazon Products Reviews

Sentiment analysis and opinion mining of Reddit data.

Python AI assistant 🧠

Watcher - Open Source Cybersecurity Threat Hunting Platform. Developed with Django & React JS.

텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지)

maximum entropy based part-of-speech tagger for NLTK

Front-end speech processing aims at extracting proper features from short- term segments of a speech utterance, known as frames. It is a pre-requisite step toward any pattern recognition problem employing speech or audio (e.g., music). Here, we are interesting in voice disorder classification. That is, to develop two-class classifiers, which can discriminate between utterances of a subject suffering from say vocal fold paralysis and utterances of a healthy subject.The mathematical modeling of the speech production system in humans suggests that an all-pole system function is justified [1-3]. As a consequence, linear prediction coefficients (LPCs) constitute a first choice for modeling the magnitute of the short-term spectrum of speech. LPC-derived cepstral coefficients are guaranteed to discriminate between the system (e.g., vocal tract) contribution and that of the excitation. Taking into account the characteristics of the human ear, the mel-frequency cepstral coefficients (MFCCs) emerged as descriptive features of the speech spectral envelope. Similarly to MFCCs, the perceptual linear prediction coefficients (PLPs) could also be derived. The aforementioned sort of speaking tradi- tional features will be tested against agnostic-features extracted by convolu- tive neural networks (CNNs) (e.g., auto-encoders) [4]. The pattern recognition step will be based on Gaussian Mixture Model based classifiers,K-nearest neighbor classifiers, Bayes classifiers, as well as Deep Neural Networks. The Massachussets Eye and Ear Infirmary Dataset (MEEI-Dataset) [5] will be exploited. At the application level, a library for feature extraction and classification in Python will be developed. Credible publicly available resources will be 1used toward achieving our goal, such as KALDI. Comparisons will be made against [6-8].

Simple chatbot in Python using NLTK and scikit-learn

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

Natural Language Processing notes and implementations.

NLTK Source

🎤 Lyrics/associated NLP data for Billboard's Top 100, 1950-2015.

🍊 📄 Text Mining add-on for Orange3

Extracts character names from a text file and performs analysis of text sentences containing the names.

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.

NLTK Data

Sentiment Analysis on the First Republic Party debate in 2016 based on Python,NLTK and ML.

An introduction to Natural Language processing using NLTK with python.

Python tutorials as Jupyter Notebooks for NLP, ML, AI

Introdução à Recuperação de Informações

Extensive tutorials for the Advanced NLP Workshop in Open Data Science Conference Europe 2020. We will leverage machine learning, deep learning and deep transfer learning to learn and solve popular tasks using NLP including NER, Classification, Recommendation \ Information Retrieval, Summarization, Classification, Language Translation, Q&A and T…

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

Aspect-Based Sentiment Analysis

The Classical Language Toolkit

Repo containing the Twitter preprocessor module, developed by the AUTH OSWinds team

API server for NLTK