Search Results for "machine learning predictive"

Showing 965 open source projects for "machine learning predictive"

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  • 1
    NBA Sports Betting Machine Learning

    NBA Sports Betting Machine Learning

    NBA sports betting using machine learning

    NBA-Machine-Learning-Sports-Betting is an open-source Python project that applies machine learning techniques to predict outcomes of National Basketball Association games for analytical and betting-related research. The system gathers historical team statistics and game data spanning multiple seasons, beginning with the 2007–2008 NBA season and continuing through the present.
    Downloads: 11 This Week
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  • 2
    machine-learning-refined

    machine-learning-refined

    Master the fundamentals of machine learning, deep learning

    machine-learning-refined is an educational repository designed to help students and practitioners understand machine learning algorithms through intuitive explanations and interactive examples. The project accompanies a series of textbooks and teaching materials that focus on making machine learning concepts accessible through visual demonstrations and simple code implementations.
    Downloads: 2 This Week
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  • 3
    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: 8 This Week
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  • 4
    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: 1 This Week
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  • 5
    machine learning tutorials

    machine learning tutorials

    machine learning tutorials (mainly in Python3)

    machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem.
    Downloads: 0 This Week
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  • 6
    Machine learning algorithms

    Machine learning algorithms

    Minimal and clean examples of machine learning algorithms

    Machine learning algorithms is an open-source repository that provides minimal and clean implementations of machine learning algorithms written primarily in Python. The project focuses on demonstrating how fundamental machine learning methods work internally by implementing them from scratch rather than relying on high-level libraries.
    Downloads: 0 This Week
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  • 7
    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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  • 8
    Nixtla TimeGPT

    Nixtla TimeGPT

    TimeGPT-1: production ready pre-trained Time Series Foundation Model

    ...It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code. Whether you're a bank forecasting market trends or a startup predicting product demand, TimeGPT democratizes access to cutting-edge predictive insights, eliminating the need for a dedicated team of machine learning engineers. A generative model for time series. TimeGPT is capable of accurately predicting various domains such as retail, electricity, finance, and IoT.
    Downloads: 8 This Week
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  • 9
    PySINDy

    PySINDy

    A package for the sparse identification of nonlinear dynamical systems

    ...The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a system evolves over time. This approach is particularly valuable in scientific fields such as physics, engineering, and biology where researchers seek both predictive accuracy and theoretical insight. The library provides tools for constructing libraries of candidate functions, performing sparse regression, and validating discovered models against observed data. ...
    Downloads: 3 This Week
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  • 10
    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: 0 This Week
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  • 11
    pycm

    pycm

    Multi-class confusion matrix library in Python

    PyCM is a multi-class confusion matrix library written in Python that supports both input data vectors and direct matrix, and a proper tool for post-classification model evaluation that supports most classes and overall statistics parameters. PyCM is the swiss-army knife of confusion matrices, targeted mainly at data scientists that need a broad array of metrics for predictive models and an accurate evaluation of large variety of classifiers.
    Downloads: 1 This Week
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  • 12
    Machine Learning Engineering Open Book

    Machine Learning Engineering Open Book

    Machine Learning Engineering Open Book

    Machine Learning Engineering Open Book is an open “living book” that captures practical methodologies, tooling advice, and operational knowledge for successfully training and deploying large language models and multimodal systems. The repository functions as a field guide compiled from real-world experience, particularly from work on large-scale models such as BLOOM-176B and IDEFICS-80B.
    Downloads: 2 This Week
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  • 13
    Book5_Essentials-Probability-Statistics

    Book5_Essentials-Probability-Statistics

    The book 5 of statistics in simplicity

    Book5_Essentials-of-Probability-and-Statistics is a Visualize-ML educational volume that introduces the statistical and probabilistic concepts underpinning modern data analysis and machine learning. The repository explains topics such as distributions, sampling, inference, and uncertainty using visual demonstrations and intuitive narratives. Its teaching philosophy prioritizes conceptual clarity over heavy formalism, making statistical thinking more approachable for beginners. The material connects probability theory directly to real analytical workflows, helping learners understand how statistics supports predictive modeling. ...
    Downloads: 0 This Week
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  • 14
    Orion

    Orion

    A machine learning library for detecting anomalies in signals

    Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations.
    Downloads: 8 This Week
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  • 15
    AI Hedge Fund

    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 ready-to-use financial product, giving learners insight into the mechanics of quantitative finance automation. ...
    Downloads: 3 This Week
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  • 16
    The Hundred-Page Machine Learning Book

    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. ...
    Downloads: 3 This Week
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  • 17
    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: 5 This Week
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  • 18
    Transfer Learning Repo

    Transfer Learning Repo

    Transfer learning / domain adaptation / domain generalization

    Transfer Learning Repo is an open-source repository that compiles resources, code implementations, and academic references related to transfer learning and its related research areas. The project functions as a large knowledge hub that organizes papers, tutorials, datasets, and software implementations across topics such as domain adaptation, domain generalization, multi-task learning, and few-shot learning. The repository includes surveys and theoretical explanations that help readers...
    Downloads: 0 This Week
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  • 19
    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: 6 This Week
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  • 20
    AtomAI

    AtomAI

    Deep and Machine Learning for Microscopy

    AtomAI is a Pytorch-based package for deep and machine-learning analysis of microscopy data that doesn't require any advanced knowledge of Python or machine learning. The intended audience is domain scientists with a basic understanding of how to use NumPy and Matplotlib. It was developed by Maxim Ziatdinov at Oak Ridge National Lab. The purpose of the AtomAI is to provide an environment that bridges the instrument-specific libraries and general physical analysis by enabling the seamless deployment of machine learning algorithms including deep convolutional neural networks, invariant variational autoencoders, and decomposition/unmixing techniques for image and hyperspectral data analysis. ...
    Downloads: 6 This Week
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  • 21
    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: 5 This Week
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  • 22
    TabPFN

    TabPFN

    Foundation Model for Tabular Data

    TabPFN is an open-source machine learning system that introduces a foundation model designed specifically for tabular data analysis. The model is based on transformer architectures and implements a prior-data fitted network that can perform supervised learning tasks such as classification and regression with minimal configuration. Unlike many traditional machine learning workflows that require extensive hyperparameter tuning and training cycles, TabPFN is pre-trained to perform inference directly on tabular datasets. ...
    Downloads: 7 This Week
    Last Update:
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  • 23
    Karpathy

    Karpathy

    An agentic Machine Learning Engineer

    karpathy is an experimental agentic machine learning engineer framework designed to automate many aspects of the ML development workflow. The project sets up a sandboxed environment where an AI agent can access datasets, run experiments, and generate machine learning artifacts through a web interface. Its startup script automatically prepares the environment by creating a sandbox directory, installing key ML libraries, and launching the agent interface. ...
    Downloads: 2 This Week
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  • 24
    EconML

    EconML

    Python Package for ML-Based Heterogeneous Treatment Effects Estimation

    EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal of combining state-of-the-art machine learning techniques with econometrics to bring automation to complex causal inference problems. One of the biggest promises of machine learning is to automate decision-making in a multitude of domains. ...
    Downloads: 8 This Week
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  • 25
    Coursera-ML-AndrewNg-Notes

    Coursera-ML-AndrewNg-Notes

    Personal notes from Wu Enda's machine learning course

    Coursera-ML-AndrewNg-Notes is an open-source repository that provides detailed study notes and explanations for Andrew Ng’s well-known machine learning course. The project aims to help students understand the mathematical concepts, algorithms, and intuition behind fundamental machine learning techniques taught in the course. It organizes the material into clear written summaries that accompany each lecture topic, including supervised learning, regression methods, neural networks, and optimization algorithms. ...
    Downloads: 2 This Week
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