A compute framework for turning complex data into vectors. Build multimodal vectors with ease and define weights at query time so you don't need a custom reranking algorithm to optimise results. Go straight from notebook to production with the same SDK.

OCR, extract and classify documents. In addition, annotate documents and build your own NLP and Computer Vision models using Python by downloading the data. Find examples in our Colab Notebooks, e. g. how to fine-tune Flair.

💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️

A collection of notebooks for Natural Language Processing from NLP Town

Machine Learning and Deep Learning: Mini projects, notebooks of competitions, exercises and notes from courses and books.

This project explores methods to classify song lyrics by genre across two notebooks. In Notebook 1, various models (Transformer, LSTM, Random Forest) were tested, achieving accuracies up to 93.5%. Notebook 2 investigated Graph Neural Networks (GNNs) with TF-IDF and BERT embeddings, with the highest accuracy of 85.55% using GCN and BERT embeddings.

Prompts, notebooks, and tools for generative pre-trained transformers.

This repository contains a collection of script files and notebooks documenting our deep learning progress and revisions. We regularly update and push new content as we explore various concepts and deepen our understanding.

A repository for my self-learning journey on LLMs. Collection of resources, notebooks, blogs, tutorials.

Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).

A Repo to store the Google Colaboratory Notebooks that I have created and shared

NLP demos and talks made with Jupyter Notebook and reveal.js

my notebooks for miscellaneous projects 📖

Colab notebooks for semantic search system

The Sentiment Analysis Model is a TensorFlow-based project that predicts text sentiment. Trained on Twitter data, it can be customized with other datasets for personalized sentiment predictions. The repository includes a single Jupyter Notebook with complete code for preprocessing, model training, and prediction.

The Next-Word Prediction Model uses TensorFlow to predict the next word in a sentence. Trained on a book PDF, it can be fine-tuned with your dataset. The repository includes a single Jupyter Notebook with the code for preprocessing and model training.

A notebook on NLP sentiment analysis for text classification of game reviews between "positive", "neutral" and "negative".

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BER

A collection of Colab/Jupyter Notebooks for NLP, collection, analysis, and visualization.

It includes steps such as text pre-processing, document indexing, and query processing using the NLTK library and other NLP tools in the Jupyter Notebook environment. The Cranfield collection was used in the project.