Popular GitHub Repositories for Preprocess

kapre: Keras Audio Preprocessors

Toolkit to obtain and preprocess German text corpora, train models and evaluate them with generated testsets. Built with Gensim and Tensorflow.

Feature extraction of speech signal is the initial stage of any speech recognition system.

Speed up image preprocess with cuda when handle image or tensorrt inference

A Word Level Transformer layer based on PyTorch and ? Transformers.

Its an open source code to easily preprocess your images for mapping faces and convert a tfrecord , csv file to train your model.

In this course navigates through the LLMOps pipeline, enabling you to preprocess training data for supervised fine-tuning and deploy custom Large Language Models (LLMs).

A fast framework for pre-processing (Cleaning text, Reduction of vocabulary, Feature extraction and Vectorization). Implemented with parallel processing using custom number of processes.

A package to download and preprocess a Wikipedia dump, in any language.

Relational NLP: Convert text into relational facts.

The contents of this repository showcase how to extract table data from a PDF file and preprocess it to facilitate word embedding. This preprocessing step enhances the readability of table data for language models and enables us to extract more contextual information from the tables.

Library/framework for making predictions. Automatically choose best models (ARIMA, regressions, MLP, LSTM...) from libraries like Scikit, Statsmodels or Tensorflow. Preprocess data and chose optimal parameters of prediction.

Here in this system it discloses a log analysis method based on deep learning for an intrusion detection system, which includes the following steps: preprocess the acquired logs of different types in the target system; perform log analysis on the preprocessed logs using a clustering-based method; then, encode the parsed log events into digital feature vectors, use LSTM-based neural network and log collect-based clustering methods to learn the encoded logs to form warning information.

Quickly preprocesses Japanese text using NLP/NER from SpaCy for Japanese translation or other NLP tasks.

Some useful examples of Deep Learning (.ipynb)

The Automated ML web app project leverages Python along with Pandas Profiling, PyCaret, and Streamlit to provide a seamless and user-friendly experience for automating machine learning workflows. It enables users to effortlessly explore, preprocess, model, and download the trained model

Explore credit card approval prediction through data analysis and machine learning. Preprocess data, train logistic regression models, and optimize hyperparameters. Learn data preprocessing, feature engineering, model training, and evaluation. Dive into the world of machine learning with Python and popular libraries.

Configurable tools to easily preprocess your data for data science and machine learning.

This project applies Multi-Layer Perceptrons (MLPs) using PyTorch to predict patient no-shows for medical appointments. We preprocess the dataset, optimize MLP architectures, and enhance prediction accuracy through advanced techniques.

Preprocess a sample text by performing word and sentence tokenization, stopword removal, and stemming