Personal Lab Notebooks
-
Updated
Aug 7, 2024 - Jupyter Notebook
Personal Lab Notebooks
Jupyter notebooks on Natural Language Processing.
Source Code Analysis of Jupyter Notebooks using Natural Language Processing
This repository contains deep learning resources and projects, including FreeCodeCamp certification challenge solutions, curated documentation, algorithm and library explorations, NLP implementations, and structured input-output experiments using Jupyter notebooks.
💬 A hands-on collection of Jupyter notebooks exploring essential Natural Language Processing (NLP) concepts including tokenization, stop words, Bag of Words, TF-IDF, POS tagging, NER, SpaCy pipelines, stemming, lemmatization, and word embeddings with FastText and Gensim.
🤖💻This repository showcases a comprehensive Natural Language Processing (NLP) pipeline implemented in Python using Jupyter notebooks. The pipeline deploys various machine learning techniques to classify labeled dataset. The pipeline employs comparisons of the dataset using Recurrent Neural Network (RNN) and RandomForest Classifier algorithms.
EEA Jupyter Notebook Data Science Stack
Some AI notebooks didactic applications
A few Jupyter notebooks about Natural Language Processing
A Jupyter notebook analyzing the major reasons for Tesla order cancellation and how Elon Musk's tweets correlate with order cancellation.
Jupyter Notebook kernels containing EDA, NLP analysis and Recommender system
A jupyter notebook for topic-modelling, clustering and question-answering on COVID-19 research papers.
Topic modelling - optimization of model hyper params. Notebooks are examples of using our optimization pipeline for sample data.
Python Notebooks for Collecting Tweets and Analyze their text using various text classification and clustering techniques
A comprehensive set of Jupyter notebooks that take you from NLP fundamentals to advanced techniques. Covers text preprocessing, POS tagging, NER, sentiment analysis (with VADER), text classification, word embeddings, and transformer models like BERT. Built with real-world datasets using NLTK, spaCy, scikit-learn, and Hugging Face Transformers.
A Jupyter notebook on implementation of Latent Semantic Analysis (A Topic Modelling Algorithm) in python.
Introducing Natural Language Processing (NLP) with jupyter notebooks.
This repository contains various models for text summarization tasks. Each model has a separate directory containing the implementation code, pretrained weights, and a Jupyter notebook for testing the model on sample input texts. Feel free to use these models for your own text summarization tasks or to experiment with them further.
📓 Long(er) text representation and classification using Doc2Vec embeddings
Add a description, image, and links to the gensim topic page so that developers can more easily learn about it.
To associate your repository with the gensim topic, visit your repo's landing page and select "manage topics."