Showing 1012 open source projects for "machine learning python"

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  • 1
    Best-of Machine Learning with Python

    Best-of Machine Learning with Python

    A ranked list of awesome machine learning Python libraries

    ...If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! General-purpose machine learning and deep learning frameworks.
    Downloads: 1 This Week
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  • 2
    Homemade Machine Learning

    Homemade Machine Learning

    Python examples of popular machine learning algorithms

    homemade-machine-learning is a repository by Oleksii Trekhleb containing Python implementations of classic machine-learning algorithms done “from scratch”, meaning you don’t rely heavily on high-level libraries but instead write the logic yourself to deepen understanding. Each algorithm is accompanied by mathematical explanations, visualizations (often via Jupyter notebooks), and interactive demos so you can tweak parameters, data, and observe outcomes in real time. ...
    Downloads: 0 This Week
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  • 3
    Interpretable machine learning

    Interpretable machine learning

    Book about interpretable machine learning

    This book is about interpretable machine learning. Machine learning is being built into many products and processes of our daily lives, yet decisions made by machines don't automatically come with an explanation. An explanation increases the trust in the decision and in the machine learning model. As the programmer of an algorithm you want to know whether you can trust the learned model.
    Downloads: 6 This Week
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  • 4
    Synapse Machine Learning

    Synapse Machine Learning

    Simple and distributed Machine Learning

    SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit, and OpenCV. ...
    Downloads: 0 This Week
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  • 5
    SageMaker Python SDK

    SageMaker Python SDK

    Training and deploying machine learning models on Amazon SageMaker

    SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training.
    Downloads: 0 This Week
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  • 6
    MNE-Python

    MNE-Python

    Magnetoencephalography (MEG) and Electroencephalography EEG in Python

    Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data. MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more.
    Downloads: 1 This Week
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  • 7
    River ML

    River ML

    Online machine learning in Python

    River is a Python library for online machine learning. It aims to be the most user-friendly library for doing machine learning on streaming data. River is the result of a merger between creme and scikit-multiflow.
    Downloads: 8 This Week
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  • 8
    Awesome production machine learning

    Awesome production machine learning

    Curated list of awesome open source libraries

    This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, version, scale, and secure your production machine learning. Open-source frameworks, tutorials, and articles curated by machine learning professionals. Open-source bias audit toolkits for data scientists, machine learning researchers, and policymakers to audit machine learning models for discrimination and bias, and to make informed and equitable decisions around developing and deploying predictive risk-assessment tools.
    Downloads: 1 This Week
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  • 9
    scikit-learn

    scikit-learn

    Machine learning in Python

    scikit-learn is an open source Python module for machine learning built on NumPy, SciPy and matplotlib. It offers simple and efficient tools for predictive data analysis and is reusable in various contexts.
    Downloads: 10 This Week
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  • 10
    PyTorch

    PyTorch

    Open source machine learning framework

    ...PyTorch can be used as a replacement for Numpy, or as a deep learning research platform that provides optimum flexibility and speed.
    Downloads: 105 This Week
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  • 11
    Alibi Explain

    Alibi Explain

    Algorithms for explaining machine learning models

    Alibi is a Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-quality implementations of black-box, white-box, local and global explanation methods for classification and regression models.
    Downloads: 4 This Week
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  • 12
    Keras

    Keras

    Python-based neural networks API

    Python Deep Learning library
    Downloads: 7 This Week
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  • 13
    PyCaret

    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. ...
    Downloads: 3 This Week
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  • 14
    Learning Interpretability Tool

    Learning Interpretability Tool

    Interactively analyze ML models to understand their behavior

    The Learning Interpretability Tool (LIT, formerly known as the Language Interpretability Tool) is a visual, interactive ML model-understanding tool that supports text, image, and tabular data. It can be run as a standalone server, or inside of notebook environments such as Colab, Jupyter, and Google Cloud Vertex AI notebooks.
    Downloads: 1 This Week
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  • 15
    tslearn

    tslearn

    The machine learning toolkit for time series analysis in Python

    The machine learning toolkit for time series analysis in Python. tslearn expects a time series dataset to be formatted as a 3D numpy array. The three dimensions correspond to the number of time series, the number of measurements per time series and the number of dimensions respectively (n_ts, max_sz, d). In order to get the data in the right format.
    Downloads: 3 This Week
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  • 16
    tika-python

    tika-python

    Python binding to the Apache Tika™ REST services

    A Python port of the Apache Tika library that makes Tika available using the Tika REST Server. This makes Apache Tika available as a Python library, installable via Setuptools, Pip and easy to install. To use this library, you need to have Java 7+ installed on your system as tika-python starts up the Tika REST server in the background. To get this working in a disconnected environment, download a tika server file (both tika-server.jar and tika-server.jar.md5, which can be found here) and set...
    Downloads: 0 This Week
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  • 17
    Mlxtend

    Mlxtend

    A library of extension and helper modules for Python's data analysis

    Mlxtend (machine learning extensions) is a Python library of useful tools for day-to-day data science tasks.
    Downloads: 2 This Week
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  • 18
    TPOT

    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.
    Downloads: 0 This Week
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  • 19
    AmpliGraph

    AmpliGraph

    Python library for Representation Learning on Knowledge Graphs

    Open source library based on TensorFlow that predicts links between concepts in a knowledge graph. AmpliGraph is a suite of neural machine learning models for relational Learning, a branch of machine learning that deals with supervised learning on knowledge graphs.
    Downloads: 0 This Week
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  • 20
    huggingface_hub

    huggingface_hub

    The official Python client for the Huggingface Hub

    The huggingface_hub library allows you to interact with the Hugging Face Hub, a platform democratizing open-source Machine Learning for creators and collaborators. Discover pre-trained models and datasets for your projects or play with the thousands of machine-learning apps hosted on the Hub. You can also create and share your own models, datasets, and demos with the community. The huggingface_hub library provides a simple way to do all these things with Python.
    Downloads: 8 This Week
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  • 21
    tvm

    tvm

    Open deep learning compiler stack for cpu, gpu, etc.

    Apache TVM is an open source machine learning compiler framework for CPUs, GPUs, and machine learning accelerators. It aims to enable machine learning engineers to optimize and run computations efficiently on any hardware backend. The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging machine learning models for any hardware platform. ...
    Downloads: 2 This Week
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  • 22
    BindsNET

    BindsNET

    Simulation of spiking neural networks (SNNs) using PyTorch

    A Python package used for simulating spiking neural networks (SNNs) on CPUs or GPUs using PyTorch Tensor functionality. BindsNET is a spiking neural network simulation library geared towards the development of biologically inspired algorithms for machine learning. This package is used as part of ongoing research on applying SNNs to machine learning (ML) and reinforcement learning (RL) problems in the Biologically Inspired Neural & Dynamical Systems (BINDS) lab.
    Downloads: 0 This Week
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  • 23
    Gradio

    Gradio

    Create UIs for your machine learning model in Python in 3 minutes

    Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere! Gradio can be installed with pip. Creating a Gradio interface only requires adding a couple lines of code to your project. You can choose from a variety of interface types to interface your function. Gradio can be embedded in Python notebooks or presented as a webpage.
    Downloads: 17 This Week
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  • 24
    TensorFlow Privacy

    TensorFlow Privacy

    Library for training machine learning models with privacy for data

    Library for training machine learning models with privacy for training data. This repository contains the source code for TensorFlow Privacy, a Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy. The library comes with tutorials and analysis tools for computing the privacy guarantees provided.
    Downloads: 0 This Week
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  • 25
    Adversarial Robustness Toolbox

    Adversarial Robustness Toolbox

    Adversarial Robustness Toolbox (ART) - Python Library for ML security

    Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, sci-kit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio, video, etc.) and machine learning tasks (classification, object detection, generation, certification, etc.).
    Downloads: 0 This Week
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