294 skills found · Page 9 of 10
aniass / Sentiment Analysis ReviewsSentiment analysis of women's clothes reviews by using machine learning algorithms and Neural Networks (LSTM).
sachinl0har / Acro ChatbotChatbot using Django
Prakashdeveloper03 / SMS Spam ClassifierSMS Spam Classifier app is used to predict if the given input message is spam or not created using python's scikit-learn, fastapi, pandas, nltk and joblib packages.
Abdullahw72 / E Commerce ChatbotChatbot for E-Commerce Related Questions
DemetersSon83 / Spacy Affect ModelA Spacy model for measuring emotional affect.
simranjeet97 / GenAI HyperPersonalisationI’ll break down how hyperpersonalization is reshaping industries, from finance to banking, and how you can build your very own hyperpersonalization web app using Python, Machine Learning, Generative AI (GenAI), and open-source LLMs from Hugging Face.
Magnus167 / JarPhysjarPhys is an image scraping app intended to scrape and search text data from notes (handwritten & typed) and courseware
VoxDroid / NLP Email CategorizerAn efficient text classification pipeline for email subjects, leveraging NLP techniques and Multinomial Naive Bayes. Easily preprocess data, train the model, and categorize new email subjects. Ideal for NLP enthusiasts and those building practical email categorization systems using Python.
NishthaChaudhary / Text Data Analysis For CoMeDiAnS NLP ProjectNatural language processing (NLP) is an exciting branch of artificial intelligence (AI) that allows machines to break down and understand human language. I plan to walk through text pre-processing techniques, machine learning techniques and Python libraries for NLP. Text pre-processing techniques include tokenization, text normalization and data cleaning. Once in a standard format, various machine learning techniques can be applied to better understand the data. This includes using popular modeling techniques to classify emails as spam or not, or to score the sentiment of a tweet on Twitter. Newer, more complex techniques can also be used such as topic modeling, word embeddings or text generation with deep learning. We will walk through an example in Jupyter Notebook that goes through all of the steps of a text analysis project, using several NLP libraries in Python including NLTK, TextBlob, spaCy and gensim along with the standard machine learning libraries including pandas and scikit-learn.
AnilSener / Python NLTK Exercise Sentiwordnet Scoringpython-NLP-Simple Sentiment Analysis
Akirato / Lesk AlgorithmPython Implementation of Lesk Algorithm using nltk wordnet
szyku / Nltk ApiSimple python's NLTK API. Provides lexical functionalities like dictionary, synonyms, and lemmatization.
Tharun-tharun / AI Chatbot Framework Using NLTKA python chatbot framework with Natural Language Understanding and Artificial Intelligence (using NLTK) 💬
iamhimanshu0 / NLTK PythonLearn to perform Natural Language Processing with NLTK. We will perform tasks like NLTK tokenize, removing stop words, stemming NLTK, lemmatization NLTK, finding synonyms and antonyms, and more.
fdjingyuan / NLP NltkNLP course at Fudan & nltk-python
AmirhosseinDotZip / SNSa simple search engine in python using the nltk library
gustavecortal / NgramPython implementation of n-gram language models from scratch and using NLTK (+ slides from my NLP course)
chandantr / Metaphor DetectionAn application of Stanford parser and the Python nltk library to detect Noun-Noun metaphors in sentences
ninadpatil09 / NLP NotebooksExplore NLP tasks with Python using NLTK, SpaCy & scikit-learn: Tokenization, Normalization, NER, POS tagging, Encoding, Word embedding.
josejesusguzman / Meetup Github Chatgpt PlnClase de fundamentos de procesamiento de lenguaje natural
