Search Results for "machine learning predictive"

Showing 2301 open source projects for "machine learning predictive"

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    Empower Your Contact Center with Human-Like AI Conversations

    Deliver faster resolutions, lower costs, and better CX without hiring another agent.

    Enterprise Bot, based in Switzerland, is a pioneer in Conversational AI, Process Automation, and Generative AI. With the trust of esteemed enterprise giants across industries like Generali, SIX, SBB, DHL, and SWICA, Enterprise Bot is revolutionizing both customer and employee experiences. Through its advanced integration with Large Language Models (LLM) such as ChatGPT and Llama 2, and its unique patent-pending DocBrain technology, the company delivers unparalleled personalization, active engagement, and omnichannel solutions across platforms like email, voice, and chat. Furthermore, Enterprise Bot integrates with existing core systems, such as SAP, CRMs, Confluence and more, and with its proprietary middleware, Blitzico, enables the AI to not only respond to queries but also take action to resolve them. This dedication to innovation in four main use case areas, Customer Support, Sales and Marketing, Knowledge Management and Digital Coworker, elevates both CX and employee productivity.
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  • Estimating Software for Heavy Construction Icon
    Estimating Software for Heavy Construction

    Developed specifically for civil construction

    Built by an estimator, SharpeSoft Estimator is a fully comprehensive software that allows for a more efficient and quicker job-winning bids. Ideal for civil, utility, heavy/highway, grading, excavating, paving, and pipeline contractors, SharpeSoft Estimator offers advanced features such as Item Master, Subcontractor Comparison, Materials Comparison, Grouped Items, Trench Profiler, Haul Calculations, What-if Scenarios, Batch Reports, and more.
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  • 1
    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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  • 2
    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: 2 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: 2 This Week
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  • 4
    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: 15 This Week
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  • The Most Awarded Employee Time Clock Software Icon
    The Most Awarded Employee Time Clock Software

    For businesses who have employees they need to track time, attendance, or schedule.

    Cloud based time clock solution that pre-populates reports for payroll. Employees can punch in on their desktop or mobile devices. Punching in & out is intuitive for your employees & easy for you to view & export time. Employees can clock in using a browser or our Google, iOS, & Android apps. You can view who's working, their GPS position or even limit where they can punch. We integrate with QuickBooks, ADP, Paychex, & SurePayroll while also offering Excel exports. Advanced features such as PTO Accrual Tracking, Punch Rounding, Job Codes, QR Codes, Automatic Breaks, & SSO are all included in our cloud based time clock.
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  • 5
    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: 1 This Week
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  • 6
    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: 0 This Week
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  • 7
    Machine Learning Study

    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.
    Downloads: 0 This Week
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  • 8
    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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  • 9
    Machine learning basics

    Machine learning basics

    Plain python implementations of basic machine learning algorithms

    Machine learning basics repository is an educational project that provides plain Python implementations of fundamental machine learning algorithms designed to help learners understand how these methods work internally. Instead of relying on external machine learning libraries, the algorithms are implemented from scratch so that users can explore the mathematical logic and computational structure behind each technique.
    Downloads: 0 This Week
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  • Easy-to-Use Website Accessibility Widget Icon
    Easy-to-Use Website Accessibility Widget

    An accessibility solution for quick website accessibility improvement.

    All in One Accessibility is an AI based accessibility tool that helps organizations to enhance the accessibility and usability of websites quickly.
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  • 10
    Machine Learning Foundations

    Machine Learning Foundations

    Machine Learning Foundations: Linear Algebra, Calculus, Statistics

    Machine Learning Foundations repository contains the code, notebooks, and teaching materials used in Jon Krohn’s Machine Learning Foundations curriculum. The project focuses on explaining the fundamental mathematical and computational concepts that underpin modern machine learning and artificial intelligence systems. The materials cover essential topics such as linear algebra, calculus, statistics, and probability, which form the theoretical basis of many machine learning algorithms. ...
    Downloads: 0 This Week
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  • 11
    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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  • 12
    Machine Learning Zoomcamp

    Machine Learning Zoomcamp

    Learn ML engineering for free in 4 months

    Machine Learning Zoomcamp is an open-source repository containing the materials for a comprehensive course that teaches machine learning engineering from fundamentals to deployment. The project is designed to guide learners through the complete lifecycle of developing machine learning systems, starting with data preparation and model training and ending with production deployment.
    Downloads: 0 This Week
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  • 13
    Machine Learning Systems

    Machine Learning Systems

    Introduction to Machine Learning Systems

    Machine Learning Systems is an open educational repository that serves as the source and learning stack for the Machine Learning Systems textbook, a project focused on teaching how to engineer AI systems that work reliably in real-world environments. Rather than concentrating only on model training, the material emphasizes the broader discipline of AI engineering, covering efficiency, reliability, deployment, and evaluation across the full lifecycle of intelligent systems. ...
    Downloads: 0 This Week
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  • 14
    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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  • 15
    Machine Learning Octave

    Machine Learning Octave

    MatLab/Octave examples of popular machine learning algorithms

    This repository contains MATLAB / Octave implementations of popular machine learning algorithms, along with explanatory code and mathematical derivations, intended as educational material rather than production code. Implementations of supervised learning algorithms (linear regression, logistic regression, neural nets). The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls.
    Downloads: 0 This Week
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  • 16
    learning

    learning

    A log of things I'm learning

    The learning repository by Amit Chaudhary is a continuously updated log of concepts, technologies, and skills related to software engineering and computer science. Rather than being a traditional software library, the repository acts as a structured knowledge base documenting the author’s ongoing learning journey across topics such as programming, system design, machine learning, and generative AI.
    Downloads: 0 This Week
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  • 17
    Machine Learning Notebooks

    Machine Learning Notebooks

    Machine Learning Notebooks

    Machine Learning Notebooks is an open-source collection of machine learning notebooks designed to provide practical, minimal, and reusable implementations of common AI tasks across different domains. The project focuses on delivering concise, well-structured Jupyter notebooks that demonstrate how to build, train, and evaluate models using modern machine learning frameworks such as PyTorch.
    Downloads: 0 This Week
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  • 18
    The Machine & Deep Learning Compendium

    The Machine & Deep Learning Compendium

    List of references in my private & single document

    The Machine & Deep Learning Compendium is an open-source knowledge repository that compiles summaries, references, and learning materials related to machine learning and deep learning. The project functions as a comprehensive compendium that organizes hundreds of topics covering algorithms, frameworks, research areas, and practical machine learning workflows.
    Downloads: 0 This Week
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  • 19
    Zero to Mastery Machine Learning

    Zero to Mastery Machine Learning

    All course materials for the Zero to Mastery Machine Learning

    Zero to Mastery Machine Learning is an open-source repository that contains the complete course materials for the Zero to Mastery Machine Learning and Data Science bootcamp. The project provides a structured curriculum designed to teach machine learning and data science using Python through hands-on projects and interactive notebooks. The repository includes datasets, Jupyter notebooks, documentation, and example code that walk learners through the entire machine learning workflow from problem definition to model deployment. ...
    Downloads: 7 This Week
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  • 20
    caret

    caret

    caret (Classification And Regression Training) R package

    The caret (Classification And Regression Training) R package streamlines the process of building predictive machine learning models. It provides uniform interfaces for model training, tuning, evaluation, preprocessing, and variable importance. With support for over 200 models, caret is foundational for R workflows in modeling and machine learning.
    Downloads: 2 This Week
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  • 21
    Machine Learning Tutorials Repository

    Machine Learning Tutorials Repository

    Dive deep into the realms of Machine Learning and other topics

    The Machine Learning Tutorials Repository is a comprehensive collection of resources, examples, and implementations designed to help users understand and apply machine learning concepts. It covers a wide range of topics, including supervised learning, unsupervised learning, neural networks, and data preprocessing techniques. The project is structured to provide both theoretical explanations and practical code examples, making it suitable for learners at different levels. ...
    Downloads: 4 This Week
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  • 22
    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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  • 23
    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: 1 This Week
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  • 24
    Interactive Machine Learning Experiments

    Interactive Machine Learning Experiments

    Interactive Machine Learning experiments

    Interactive Machine Learning Experiments is a collection of interactive demonstrations that showcase how various machine learning models can be trained and used in real applications. The project combines Jupyter or Colab notebooks with browser-based visual demos that allow users to see trained models operating in real time. Many experiments involve tasks such as image classification, object detection, gesture recognition, and simple generative models. ...
    Downloads: 0 This Week
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  • 25
    Start Machine Learning in 2026

    Start Machine Learning in 2026

    A complete guide to start and improve in machine learning

    Start Machine Learning in 2026 repository is an open educational guide designed to help beginners enter the field of machine learning and artificial intelligence with little or no prior technical background. The project organizes a large collection of learning resources, including online courses, books, tutorials, research articles, and video lectures that explain fundamental AI concepts.
    Downloads: 0 This Week
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