Displaying 1 to 20 from 28 results

awesome-ml-for-cybersecurity - :octocat: Machine Learning for Cyber Security

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A curated list of amazingly awesome tools and resources related to the use of machine learning for cyber security. Please read CONTRIBUTING if you wish to add tools or resources.

Machine-Learning-Tutorials - machine learning and deep learning tutorials, articles and other resources

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This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resources. Other awesome lists can be found in this list. If you want to contribute to this list, please read Contributing Guidelines.




awesome-datascience - :memo: An awesome Data Science repository to learn and apply for real world problems

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An open source Data Science repository to learn and apply towards solving real world problems. First of all, Data Science is one of the hottest topics on the Computer and Internet farmland nowadays. People have gathered data from applications and systems until today and now is the time to analyze them. The next steps are producing suggestions from the data and creating predictions about the future. Here you can find the biggest question for Data Science and hundreds of answers from experts. Our favorite data scientist is Clare Corthell. She is an expert in data-related systems and a hacker, and has been working on a company as a data scientist. Clare's blog. This website helps you to understand the exact way to study as a professional data scientist.

machine-learning-with-ruby - Curated list: Resources for machine learning in Ruby.

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Machine Learning is a field of Computational Science - often nested under AI research - with many practical applications due to the ability of resulting algorithms to systematically implement a specific solution without explicit programmer's instructions. Obviously many algorithms need a definition of features to look at or a biggish training set of data to derive the solution from. This curated list comprises awesome libraries, data sources, tutorials and presentations about Machine Learning utilizing the Ruby programming language.


nlp-with-ruby - Practical Natural Language Processing done in Ruby.

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This curated list comprises awesome resources, libraries, information sources about computational processing of texts in human languages with the Ruby programming language. That field is often referred to as NLP, Computational Linguistics, HLT (Human Language Technology) and can be brought in conjunction with Artificial Intelligence, Machine Learning, Information Retrieval, Text Mining, Knowledge Extraction and other related disciplines. This list comes from our day to day work on Language Models and NLP Tools. Read why this list is awesome. Our FAQ describes the important decisions and useful answers you may be interested in.

Awesome-Deep-Learning-Resources - Rough list of my favorite deep learning resources, useful for revisiting topics or for reference

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This is a rough list of my favorite deep learning resources. It has been useful to me for learning how to do deep learning, I use it for revisiting topics or for reference. I (Guillaume Chevalier) have built this list and got through all of the content listed here, carefully. You might also want to look at Andrej Karpathy's new post about trends in Machine Learning research.

Awesome-CoreML-Models - Largest list of models for Core ML (for iOS 11+)

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We've put up the largest collection of machine learning models in Core ML format, to help iOS, macOS, tvOS, and watchOS developers experiment with machine learning techniques. We've created a site with better visualization of the models CoreML.Store, and are working on more advance features. If you've converted a Core ML model, feel free to submit an issue.

useful-java-links - A list of useful Java frameworks, libraries, software and hello worlds examples

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This is a fork of awesome link with new structure, additional license info and github's star info for every link, with a lot of new links (all non-mobile github projects with 390 or more star) and so on. The russian version is in this place. The "Hello Worlds examples" project is in this place.

awesome-deep-learning-music - List of articles related to deep learning applied to music

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By Yann Bayle (Website, GitHub) from LaBRI (Website, Twitter), Univ. Bordeaux (Website, Twitter), CNRS (Website, Twitter) and SCRIME (Website). The role of this curated list is to gather scientific articles, thesis and reports that use deep learning approaches applied to music. The list is currently under construction but feel free to contribute to the missing fields and to add other resources! To do so, please refer to the How To Contribute section. The resources provided here come from my review of the state-of-the-art for my PhD Thesis for which an article is being written. There are already surveys on deep learning for music generation, speech separation and speaker identification. However, these surveys do not cover music information retrieval tasks that are included in this repository.

CatPapers - Cool vision, learning, and graphics papers on Cats!

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As reported by Cisco, 90% of net traffic will be visual, and indeed, most of the visual data are cat photos and videos. Thus, understanding, modeling and synthesizing our feline friends becomes a more and more important research problem these days, especially for our cat lovers. Cat Paper Collection is an academic paper collection that includes computer graphics, computer vision, machine learning and human-computer interaction papers that produce experimental results related to cats. If you want to add/remove a paper, please send an email to Jun-Yan Zhu (junyanz at berkeley dot edu).

awesome-sentiment-analysis - 😀😄😂😭 A curated list of Sentiment Analysis methods, implementations and misc

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Curated list of Sentiment Analysis methods, implementations and misc. The goal of this repository is to provide adequate links for scholars who want to research in this domain; and at the same time, be sufficiently accessible for developers who want to integrate sentiment analysis into their applications.

awesome-very-deep-learning - 🔥A curated list of papers and code about very deep neural networks

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awesome-very-deep-learning is a curated list for papers and code about implementing and training very deep neural networks. Value Iteration Networks are very deep networks that have tied weights and perform approximate value iteration. They are used as an internal (model-based) planning module.