Search Results for "python feature selection"
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253 projects for "python feature selection" with 1 filter applied:
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Python colorlog
A colored formatter for the python logging module
Add colors to the output of Python's logging module. This library is over a decade old and supported a wide set of Python versions for most of its life, which has made it a difficult library to add new features to. colorlog 6 may break backward compatibility so that newer features can be added more easily, but may still not accept all changes or feature requests. colorlog 4 might accept essential bug fixes but should not be considered actively maintained and will not accept any major changes or new features. -
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The Python Computer Science Degree
This is a curated list of free courses from reputable universities
The Python Computer Science Degree is a curated computer science curriculum built around free online courses. It is designed to mirror the core requirements of an undergraduate computer science degree while removing general education classes. The repository focuses on Python-friendly learning paths, making it approachable for self-taught developers who want a structured academic foundation. It includes courses from reputable institutions such as Harvard, MIT, Stanford, and Princeton. The... -
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Learn Python Regular Expressions
Learn Python Regular Expressions step by step
...Hundreds of examples show how each feature behaves in practical text-processing situations. Exercises are provided separately with complete solutions, and an interactive TUI app can be used for additional practice. The book is available as Markdown and a web edition, with PDF and EPUB versions offered separately. -
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Kaggle Solutions
Collection of Kaggle Solutions and Ideas
Kaggle Solutions is an open-source repository that compiles winning solutions, insights, and educational resources from hundreds of Kaggle data science competitions. The repository acts as a knowledge base for competitive machine learning by collecting solution write-ups, discussion threads, code notebooks, and tutorial resources shared by top Kaggle participants. Each competition entry typically includes information about the dataset, evaluation metrics, modeling strategies, and techniques... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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pyAudioAnalysis
Python Audio Analysis Library: Feature Extraction, Classification
pyAudioAnalysis is an open-source Python library designed for audio signal analysis, machine learning, and music information retrieval tasks. The project provides a collection of tools that allow developers to extract meaningful features from audio files and use those features for classification, segmentation, and analysis. The library supports multiple audio processing workflows, including feature extraction from raw audio signals, training of machine learning models, and automatic audio segmentation. ... -
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skfolio
Python library for portfolio optimization built on top of scikit-learn
skfolio is a Python library designed for portfolio optimization and financial risk management that integrates closely with the scikit-learn ecosystem. The project provides a unified machine learning-style framework for building, validating, and comparing portfolio allocation strategies using financial data. By following the familiar scikit-learn API design, the library allows quantitative researchers and developers to apply techniques such as model selection, cross-validation, and hyperparameter tuning to portfolio construction workflows. ... -
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Zendriver
A blazing fast, async-first, undetectable webscraping
...It features an async-first architecture that allows developers to build highly concurrent workflows, improving efficiency when handling multiple tasks or large-scale scraping operations. Zendriver also includes built-in utilities for managing cookies, browser profiles, and element selection, simplifying common automation tasks. -
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NetherSX2
Continuation of NetherSX2 based on AetherSX2 4248
NetherSX2-patch is a community-driven continuation and enhancement of the NetherSX2 Android PlayStation 2 emulator, itself a modded fork of the open-source AetherSX2 project originally based on PCSX2. It focuses on providing a more complete and feature-rich experience by applying patches to the upstream emulator build and removing ad-related bloat, fixing notification issues, and exposing many internal settings so users have finer control over performance and compatibility on mobile devices.... -
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ReClip
Download videos from almost any website
ReClip is a lightweight, self-hosted media downloader that provides a simple web-based interface for downloading videos and audio from a wide range of online platforms. Built around the yt-dlp engine, it supports over a thousand websites, including major platforms like YouTube, TikTok, and Instagram, allowing users to retrieve media content in various formats. The application emphasizes simplicity and minimalism, featuring a clean interface built with plain HTML, CSS, and JavaScript without... -
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lxml
The lxml XML toolkit for Python
A Python library for efficient XML and HTML processing, known for speed and compatibility. The lxml XML toolkit is a Pythonic binding for the C libraries libxml2 and libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python API, mostly compatible but superior to the well-known ElementTree API. -
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DINOv3
Reference PyTorch implementation and models for DINOv3
DINOv3 is the third-generation iteration of Meta’s self-supervised visual representation learning framework, building upon the ideas from DINO and DINOv2. It continues the paradigm of learning strong image representations without labels using teacher–student distillation, but introduces a simplified and more scalable training recipe that performs well across datasets and architectures. DINOv3 removes the need for complex augmentations or momentum encoders, streamlining the pipeline while... -
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Jev Ultrafast
A browser agent with a dynamic, indexed action space
Jev Ultrafast is an experimental browser agent built around a dynamic, indexed action space for fast web interaction. Each browser state is converted into a numbered table of currently available interactive elements. A policy chooses both an operation and a compatible target in a single network round trip. Supported actions include clicking, typing, selecting, scrolling, waiting, finishing, and reporting that a task is blocked. A small language model is invoked only when text must actually... -
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Gemini-API
Reverse-engineered Python API for Google Gemini web app
Gemini-API is a community-created asynchronous Python wrapper for the web interface of Google’s Gemini models (formerly Bard). It is the result of reverse-engineering the Gemini web app and exposing its functionality through a programmatic API. This enables developers to incorporate Gemini into Python applications, scripts, bots, or tools without relying solely on official SDKs. The wrapper supports streaming responses, model selection, and handling of the web-based authentication/session mechanisms used by Google’s interface. ... -
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Scrapy
A fast, high-level web crawling and web scraping framework
Scrapy is a fast, open source, high-level framework for crawling websites and extracting structured data from these websites. Portable and written in Python, it can run on Windows, Linux, macOS and BSD. Scrapy is powerful, fast and simple, and also easily extensible. Simply write the rules to extract the data, and add new functionality if you wish without having to touch the core. Scrapy does the rest, and can be used in a number of applications. It can be used for data mining, monitoring... -
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GraalPy
A Python 3 implementation built on GraalVM
GraalPy is a high-performance implementation of the Python language for the JVM built on GraalVM. GraalPy is a Python 3.11 compliant runtime. It has first-class support for embedding in Java and can turn Python applications into fast, standalone binaries. GraalPy is ready for production running pure Python code and has experimental support for many popular native extension modules. -
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AI Hedge Fund
An AI Hedge Fund Team
This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than a... -
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XY
Ultra-fast and customizable Python charts
XY is an interactive Python visualization library designed to handle both everyday charts and extremely large datasets. Charts can be created through a declarative API or familiar Matplotlib-style conventions. A Rust processing core dynamically determines how much data the current screen resolution actually needs to display. Large datasets can be rendered as bounded density or decimated views, while zooming retrieves finer details and original rows. Interactive capabilities include panning,... -
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Blackbird
OSINT tool for finding accounts across 600+ sites by username or email
Blackbird is an open source OSINT tool designed to search for user accounts across social networks and online platforms using a username or email address. The project focuses on helping investigators, researchers, and security professionals quickly discover where a specific identity appears on the internet. It performs reverse searches across more than 600 websites by leveraging data from the community-driven WhatsMyName project, which improves detection accuracy and reduces false positives.... -
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DINOv2
PyTorch code and models for the DINOv2 self-supervised learning
DINOv2 is a self-supervised vision learning framework that produces strong, general-purpose image representations without using human labels. It builds on the DINO idea of student–teacher distillation and adapts it to modern Vision Transformer backbones with a carefully tuned recipe for data augmentation, optimization, and multi-crop training. The core promise is that a single pretrained backbone can transfer well to many downstream tasks—from linear probing on classification to retrieval,... -
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Machine Learning Study
This repository is for helping those interested in machine learning
Machine Learning Study is an educational repository containing tutorials and study materials related to machine learning and data science using Python. The project compiles notebooks, explanatory documents, and practical code examples that illustrate common machine learning workflows. Topics covered include supervised learning algorithms, feature engineering, model training, and performance evaluation techniques. The repository is structured as a learning resource that guides readers through building machine learning models step by step. ... -
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Perfect Roadmap To Learn Data Science
Basic To Intermediate Python data science guide
Perfect Roadmap To Learn Data Science In 2025 is an extended, updated learning pathway curated for the modern data-science landscape — blending classical data-analysis, statistics, machine learning, deep learning, computer vision, NLP, as well as current deployment and MLOps practices to prepare learners for data-science careers in 2025. The roadmap is organized to guide learners systematically: starting with Python fundamentals and math/statistics, then progressing through classical machine-learning, deep-learning, data preprocessing, feature engineering, and onto domain-specific applications like computer vision or NLP, ending with deployment, real-world project construction, and best practices for production readiness. What makes it particularly valuable is its holistic nature: rather than focusing only on modeling or theory, it also addresses the broader lifecycle of data-science work, data ingestion, cleaning, EDA, feature engineering, model building, validation, deployment, etc. -
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hCaptcha Challenger
Gracefully face hCaptcha challenge with multimodal llms
hCaptcha Challenger is an open-source automation framework designed to solve hCaptcha verification challenges using computer vision models and multimodal reasoning techniques. The project integrates machine learning models capable of analyzing visual captcha tasks and identifying the correct responses required to pass the verification process. Instead of relying on third-party captcha-solving services or browser scripts, the system operates independently by using pretrained neural networks... -
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Backtrack Sampler
An easy-to-understand framework for LLM samplers
Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs. -
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Pretty Jupyter
Creates dynamic html report from jupyter notebook.
Pretty Jupyter is an easy-to-use package that allows to create beautiful & dynamic HTML reports. Most of the features require little to no work to get working and greatly improve the quality of the output report, or even the developer’s comfort when creating the report. For example, tabs make some visualizations much more comfortable. The features are integrated directly into the output page, therefore there is no need to have an interpreter running in the backend. This makes the HTML easily... -
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TabFM
scikit-learn compatible tabular foundation model
...Instead of fitting model weights to the user’s dataset, TabFM uses in-context learning by reading training examples and test rows together at inference time. The library provides scikit-learn-compatible classifier and regressor interfaces, which makes it familiar for data scientists already using Python ML workflows. It supports both JAX and PyTorch backends and can automatically download pretrained TabFM v1.0.0 weights. The project is useful for practitioners who want strong tabular predictions with less manual feature engineering, tuning, and repeated model training.
