Search Results for "python code"
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Showing 250 open source projects for "python code"
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Python Code Tutorials
The Python Code Tutorials
Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. -
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python-small-examples
Focus on creating classic Python small examples and cases
python-small-examples is an open-source educational repository that contains hundreds of concise Python programming examples designed to illustrate practical coding techniques. The project focuses on teaching programming concepts through small, focused scripts that demonstrate common tasks in data processing, visualization, and general programming. Each example highlights a specific function or programming pattern so that learners can quickly understand how to apply Python features in... -
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Python Programming Hub
Learn Python and Machine Learning from scratch
Python Programming Hub repository by Tanu-N-Prabhu is an educational resource designed to help programmers learn Python programming and data science concepts through practical examples and notebooks. The project contains a wide range of tutorials and exercises that cover Python fundamentals, programming concepts, and applied techniques for data analysis and machine learning. -
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fugue
A unified interface for distributed computing
Fugue is a unified interface for distributed computing that lets users execute Python, Pandas, and SQL code on Spark, Dask, and Ray with minimal rewrites. -
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Practical Machine Learning with Python
Master the essential skills needed to recognize and solve problems
...The repository emphasizes end-to-end workflows rather than isolated code snippets, showing how to handle common challenges like class imbalance, overfitting, hyperparameter optimization, and interpretability. By leveraging popular Python libraries such as pandas, scikit-learn, XGBoost, and visualization tools, it illustrates how to build reproducible and robust solutions that scale beyond small demos. -
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PyGAD
Source code of PyGAD, Python 3 library for building genetic algorithms
PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function. -
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The Hundred-Page Machine Learning Book
The Python code to reproduce illustrations from Machine Learning Book
The Hundred-Page Machine Learning Book is the official companion repository for The Hundred-Page Machine Learning Book written by machine learning researcher Andriy Burkov. The repository contains Python code used to generate the figures, visualizations, and illustrative examples presented in the book. Its purpose is to help readers better understand the concepts explained in the text by allowing them to run and experiment with the underlying code themselves. The book itself provides a concise overview of machine learning theory and practice, covering topics such as supervised learning, unsupervised learning, neural networks, and optimization algorithms. ... -
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Lazy Predict
Lazy Predict help build a lot of basic models without much code
Lazy Predict helps build a lot of basic models without much code and helps understand which models work better without any parameter tuning. -
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TorchRL
A modular, primitive-first, python-first PyTorch library
TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. TorchRL provides PyTorch and python-first, low and high-level abstractions for RL that are intended to be efficient, modular, documented, and properly tested. The code is aimed at supporting research in RL. Most of it is written in Python in a highly modular way, such that researchers can easily swap components, transform them, or write new ones with little effort. -
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Lepton AI
A Pythonic framework to simplify AI service building
A Pythonic framework to simplify AI service building. Cutting-edge AI inference and training, unmatched cloud-native experience, and top-tier GPU infrastructure. Ensure 99.9% uptime with comprehensive health checks and automatic repairs. -
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TPOT
A Python Automated Machine Learning tool that optimizes ML
Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. -
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MLflow
Open source platform for the machine learning lifecycle
MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). -
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Fairlearn
A Python package to assess and improve fairness of ML models
Fairlearn is a Python package that empowers developers of artificial intelligence (AI) systems to assess their system's fairness and mitigate any observed unfairness issues. Fairlearn contains mitigation algorithms as well as metrics for model assessment. Besides the source code, this repository also contains Jupyter notebooks with examples of Fairlearn usage. -
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qxresearch-event-1
Python hands on tutorial with 50+ Python Application
qxresearch-event-1 is an open-source educational repository that provides a collection of lightweight Python applications designed to demonstrate programming concepts and artificial intelligence techniques in simple and accessible examples. The repository contains dozens of small programs, many implemented with minimal lines of code, covering topics such as machine learning, graphical user interfaces, computer vision, and API integration. -
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PyCaret
An open-source, low-code machine learning library in Python
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that speeds up the experiment cycle exponentially and makes you more productive. In comparison with the other open-source machine learning libraries, PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only. -
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Elyra
Elyra extends JupyterLab with an AI centric approach
Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page. -
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Daft
Distributed DataFrame for Python designed for the cloud
...When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. Underneath its Python API, Daft is built in blazing fast Rust code. Rust powers Daft’s vectorized execution and async I/O, allowing Daft to outperform frameworks such as Spark. -
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machine_learning_examples
A collection of machine learning examples and tutorials
machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. The repository covers a wide range of topics including supervised learning, unsupervised learning, reinforcement learning, and natural language processing. ... -
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Text2Code for Jupyter notebook
A proof-of-concept jupyter extension which converts english queries
Text2Code for Jupyter notebook project is a proof-of-concept extension for Jupyter Notebook that allows users to generate Python code directly from natural language queries written in English. The tool is designed to simplify data analysis workflows by enabling users to describe their intended operation in plain language instead of manually writing code. When a user enters a textual command, the extension interprets the request and generates a corresponding Python code snippet that can be inserted into the notebook and executed automatically. ... -
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marimo
A reactive notebook for Python
marimo is an open-source reactive notebook for Python, reproducible, git-friendly, executable as a script, and shareable as an app. marimo notebooks are reproducible, extremely interactive, designed for collaboration (git-friendly!), deployable as scripts or apps, and fit for modern Pythonista. Run one cell and marimo reacts by automatically running affected cells, eliminating the error-prone chore of managing the notebook state. marimo's reactive UI elements, like data frame GUIs and plots,... -
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Ray
A unified framework for scalable computing
...Deploy your machine learning models at scale with Ray Serve, a Python-first and framework agnostic model serving framework. Scale reinforcement learning (RL) with RLlib, a framework-agnostic RL library that ships with 30+ cutting-edge RL algorithms including A3C, DQN, and PPO. Easily build out scalable, distributed systems in Python with simple and composable primitives in Ray Core. -
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deepfakes_faceswap
Deepfakes Software For All
Faceswap is the leading free and open source multi-platform deepfakes software. When faceswapping was first developed and published, the technology was groundbreaking, it was a huge step in AI development. It was also completely ignored outside of academia because the code was confusing and fragmentary. It required a thorough understanding of complicated AI techniques and took a lot of effort to figure it out. Until one individual brought it together into a single, cohesive collection. -
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StatsForecast
Fast forecasting with statistical and econometric models
...The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery of benchmarking and baseline methods, giving users flexibility in selecting forecasting approaches depending on data characteristics (trend, seasonality, intermittent demand, etc.). Its internal implementation leverages numba to compile performance-critical code to optimized machine-level instructions, which makes the models much faster than many traditional Python counterparts. -
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DeepLabCut
Implementation of DeepLabCut
...Please see the original paper and the latest work below! This package is collaboratively developed by the Mathis Group & Mathis Lab at EPFL (releases prior to 2.1.9 were developed at Harvard University). The code is freely available and easy to install in a few clicks with Anaconda (and pypi). DeepLabCut is an open-source Python package for animal pose estimation. -
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FLAML
A fast library for AutoML and tuning
FLAML is a lightweight Python library that finds accurate machine learning models automatically, efficiently and economically. It frees users from selecting learners and hyperparameters for each learner. For common machine learning tasks like classification and regression, it quickly finds quality models for user-provided data with low computational resources.
