• Machine learning - Wikipedia

    Machine learning is a field of computer science that gives computer systems the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.

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  • GitHub - josephmisiti/awesome-machine-learning: A curated ...

    For a list of free machine learning books available for download, go here. For a list of (mostly) free machine learning courses available online, go here. For a list of blogs on data science and machine learning, go here. For a list of free-to-attend meetups and local events, go here ...

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  • Introduction to Machine Learning - arXiv

    Introduction to Machine Learning 67577 - Fall, 2008 Amnon Shashua School of Computer Science and Engineering The Hebrew University of Jerusalem Jerusalem, Israel

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  • The Plural Machine and "One or more than One" Spelling Game.

    pdf The Plural Machine and "One or more than One" Spelling Game. Produced by Liz Taylor, Advisory Teacher in Suffolk and Stuart Scott.

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  • Machine Learning Market by Vertical & Service - 2022 ...

    Machine Learning Market by Vertical (BFSI, Healthcare and Life Sciences, Retail, Telecommunication, Government and Defense, Manufacturing, Energy and Utilities), Deployment Mode, Service, Organization Size, and Region - Global Forecast to 2022

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  • ATM: A distributed, collaborative, scalable system for ...

    ATM: A distributed, collaborative, scalable system for automated machine learning Thomas Swearingen, Will Drevoy, Bennett Cyphersy, Alfredo Cuesta-Infantez, Arun Ross and Kalyan Veeramachaneniy

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  • Weka (machine learning) - Wikipedia

    Description. Weka contains a collection of visualization tools and algorithms for data analysis and predictive modeling, together with graphical user interfaces for easy access to these functions.

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  • Machine Learning Flashcards

    Hundreds of digital flashcards on machine learning topics in DRM-less print-quality png, web-quality png, PDF, Anki, and SVG.

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  • A Course in Machine Learning

    A Course in Machine Learning by Hal Daumé III Machine learning is the study of algorithms that learn from data and experience. It is applied in a vast variety of application areas, from medicine to advertising, from military to pedestrian.

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  • Lecture Notes | Machine Learning - MIT OpenCourseWare

    This section provides the lecture notes from the course.

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  • mlpy - Machine Learning Python

    mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and the GNU Scientific Libraries.. mlpy provides a wide range of state-of-the-art machine learning methods for supervised and unsupervised problems and it is aimed at finding a reasonable compromise among modularity, maintainability, reproducibility, usability and ...

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  • Machine Learning Mastery With Python

    Discover how you can confidently step-through machine learning projects with python. Get your copy of Machine Learning Mastery With Python.

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  • Machine learning algorithm cheat sheet | Microsoft Docs

    Download the cheat sheet here: Machine Learning Algorithm Cheat Sheet (11x17 in.) Download and print the Machine Learning Algorithm Cheat Sheet in tabloid size to keep it handy and get help choosing an algorithm. The suggestions offered in this algorithm cheat sheet are approximate rules-of-thumb ...

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  • [1712.07897] Non-convex Optimization for Machine Learning

    Abstract: A vast majority of machine learning algorithms train their models and perform inference by solving optimization problems. In order to capture the learning and prediction problems accurately, structural constraints such as sparsity or low rank are frequently imposed or else the objective itself is designed to be a non-convex function.

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  • Master Machine Learning Algorithms

    Pull back the curtain on Machine Learning Algorithms. No math required, just step-by-step tutorials. Get your copy of Master Machine Learning Algorithms.

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  • Gaussian Processes for Machine Learning

    C. E. Rasmussen & C. K. I. Williams, Gaussian Processes for Machine Learning, the MIT Press, 2006, ISBN 026218253X. 2006 Massachusetts Institute of Technology.c

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  • How to Learn Machine Learning, The Self-Starter Way

    Machine learning can appear intimidating without a gentle introduction to its prerequisites. You don't need to be a professional mathematician or veteran programmer to learn machine learning, but you do need to have the core skills in those domains.

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  • Mastering .NET Machine Learning | PACKT Books

    Master the art of machine learning with .NET and gain insight into real-world applications

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  • Machine Learning A-Z™: Download Practice Datasets ...

    Greetings Welcome to the data repository for the Machine Learning course by Kirill Eremenko and Hadelin de Ponteves. The datasets and other supplementary materials are below.

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  • Python Machine Learning - Second Edition | PACKT Books

    Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries.

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  • Introduction to Statistical Learning

    Home: Download the book PDF (corrected 7th printing) Statistical Learning MOOC covering the entire ISL book offered by Trevor Hastie and Rob Tibshirani.

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