Data-mining Libraries

28 Components & Libraries

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Data-mining Libraries

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

4 September 2023 - Version 1.7.1 25 May 2023 - Version 1.7.0 15 September 2022 - Version 1.6.2 1 September 2022 - Version 1.6.1 24 August 2022 - Version 1.6.0 2 June 2022 - Version 1.5.0 For the late…

The "Python Machine Learning (1st edition)" book code repository and info resource

What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning ... from theory to the actual code that you can directly put into…

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Install CatBoost by following the guide for the Next you may want to investigate: If you cannot open documentation in your browser try adding yastatic.net and yastat.net to the list of allowed domain…

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Sebastian Raschka 2014-2024 To install mlxtend, just execute If you use conda, to install mlxtend just execute The mlxtend version on PyPI may always be one step behind; you can install the latest de…

A set of tools for extracting tables from PDF files helping to do data mining on (OCR-processed) scanned documents.

See the following images of the example input/output: Apache License 2.0. See LICENSE file.

Multi-class confusion matrix library in Python

Fig1. ConfusionMatrix Block Diagram After that, two scores are calculated for each confusion matrices, overall and class-based. The overall score is the average of the score of seven overall benchmar…

pyclustering is a Python, C++ data mining library.

Each algorithm is implemented using Python and C/C++ language, if your platform is not supported then Python implementation is used, otherwise C/C++. Implementation can be chosen by ccore flag (by de…

interpretable_machine_learning_with_python

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

Examples of techniques for training interpretable machine learning (ML) models, explaining ML models, and debugging ML models for accuracy, discrimination, and security. The notebooks highlight techn…

(AAAI' 20) A Python Toolbox for Machine Learning Model Combination

or: Alternatively, you could clone and run setup.py file: Initialize a group of classifiers as base estimators Initialize, fit, predict, and evaluate with Stacking See a sample output of classifier_s…

A Python toolbox/library for reality-centric machine learning/deep learning on partially-observed time series with PyTorch, including SOTA neural network models supporting tasks of imputation, classification, clustering, and forecasting on incomplete (irregularly-sampled) multivariate time series with NaN missing values/data.

At PyPOTS, things are related to coffee, which we're familiar with. Yes, this is a coffee universe! As you can see, there is a coffee pot in the PyPOTS logo. And what else? Please read on ;-) ☕️ Welc…

H2O.ai Machine Learning Interpretability Resources

Machine learning algorithms create potentially more accurate models than linear models, but any increase in accuracy over more traditional, better-understood, and more easily explainable techniques i…

🗣️ Tool to generate adversarial text examples and test machine learning models against them

This library allows you to generate texts using these methods, and simulate these kind of attacks on your machine learning models. By exposing your model to these texts offline, you will be able to b…

A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)

Simply use:

HTTP(S)/SOCKS5 Rotating Residential proxies - Code examples & General information

Welly helps with well loading, wireline logs, log quality, data science

Next, check out the tutorial notebooks.

Python class to scrape data from rightmove.co.uk and return listings in a pandas DataFrame object

Version 1.1 is available to install via Pip: Run the search on the rightmove website and copy the URL of the first results page. Create an instance of the class with the URL as the init argument. Fin…

An (un-)ethical hacking-station based on Raspberry Pi and Python

The SpyPi is a white-hat hacking-station I've created as part of my high school graduation-work (2017). The device aims at raising awareness of data protection by letting people interactively get in …

Python Data Science and Machine Learning Library for the Ethereum and ERC-20 Blockchain

This is an ongoing project. Made by Elyse Lam for the USC Viterbi Data Science Bootcamp Original py-etherscan-api was a well built scaffolding for python scripts using the Etherscan API. The examples…

DECIMER: Deep Learning for Chemical Image Recognition using Efficient-Net V2 + Transformer

The DECIMER 2.2 [5] (Deep lEarning for Chemical ImagE Recognition) project [1] was launched to address the OCSR problem with the latest computational intelligence methods to provide an automated open…

A machine learning application for emotion recognition from speech

A machine learning application for emotion recognition from speech. Language: Python 2.7 Mario Ruggieri Download Berlin DB from the link. Request DaFeX dataset following the link instructions. The co…

Exploratory Video Analytics System

EVA comes with a wide range of commonly used computer vision models. It written in Python, and it is licensed under the Apache license.

Algorithmic trading using machine learning.

This machine learning algorithm was built using Python 3 and scikit-learn with a Decision Tree Classifier. The program gathers stock data using the Google Finance API and pandas. The data is illustra…

awesome-python-machine-learning-resources

a collection of awesome machine learning and deep learning Python libraries&tools. 热门实用机器学习和深入学习Python库和工具的集合

This mathematics course is taught for the first year Ph.D. students of computer science and related areas @ZJU

This mathematics course is designed for the first year Ph.D. students of computer science and related areas. The course focuses on the methodologies, technologies, mathematics and algorithms currentl…

This repository contains resources in the form of ebooks, which are related to Data Science, Machine Learning, and similar topics.

Portfolio of data science and data analyst projects completed by me for academic, self learning, and hobby purposes.

This repository is containing portfolio of data science and data analyst projects completed by me (and sometimes with my team) for academic, self learning, and hobby purposes. Presented in the form o…

Artificial-Intelligence-Important-Documents-Collections

AI technology is significant because it allows software to do human functions—understanding, reasoning, planning, communication, and perception—increasingly effectively, efficiently, and affordably.

AI technology is significants because it allows softwares to do human functions—understanding, reasoning, planning, communication, and perception—increasingly effectively, efficiently, and affordably…