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CatBoost - open-source gradient boosting library
CatBoost is a high-performance open source library for gradient boosting on decision trees
GitHub - google/dopamine: Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research). Our design principles are: Easy experimentation: Make it easy for new users to run benchmark experiments. Flexible development: Make it easy for new users to try out res
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models, BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly conditioning on both left and right context in all layers. As a result, the pre-trained BERT model can be fine-tuned with
GitHub - guess-js/guess: 🔮 Libraries & tools for enabling Machine Learning driven user-experiences on the web
Guess.js provides libraries & tools to simplify predictive data-analytics driven approaches to improving user-experiences on the web. This data can be driven from any number of sources, including analytics or machine learning models. Guess.js aims to lower the friction of consuming and applying this thinking to all modern sites and apps, including building libraries & tools for popular workflows.
AI Experiments | Experiments with Google
VISUAL ARTISTS ✕ IMAGENArtists endlessly reimagine Alice’s Adventures in Wonderland by fine-tuning Imagen 2 in each of their unique styles.
Transfer learning - Wikipedia
Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task.[1] For example, for image classification, knowledge gained while learning to recognize cars could be applied when trying to recognize trucks. This topic is related to the psychological literature on transfer of learning, although practica
Integral Channel Featuresによる歩行者認識 - Preferred Networks Research & Development
はじめまして、新入社員の阿部です。入社して3ヶ月経ちました。 この記事では、歩行者検出の手法である Integral Channel Features について解説したいと思います。 はじめに 歩行者検出（人検出）は画像認識のメジャーな問題のひとつで、読んで字の如く画像中の歩行者を見つけるという問題です（上図）。たくさんの応用が考えられるため盛んに研究されていましたが、特に「顔検出」の実用化のメドがたった2000年代はじめから顔検出の次の問題として研究が活発になったようです。 人検出の手法の基本的なアイデアは顔検出のものと共通ですが、人検出に特有の難しさとして大きな姿勢変化や隠れが起こりやすいこと、髪型や服装、体型等に多様性があり、これらを克服するための様々な方法が研究されています。本記事では高精度かつ高速な検出手法として近頃注目されている”Integral Channel Feature
Deep Learning
Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence. This website is intended to host a variety of resources and pointers to information about Deep Learning. In these pages you will find a reading list, links to software, datasets, a list of deep learning resea
Jubatus : Distributed Online Machine Learning Framework¶
Jubatus English Japanese
Milk: Machine Learning Toolkit for Python - Luis Pedro Coelho
Out of date and unmaintained: use scikit-learn This is the code that I use for my research projects. Where can I get it? Github as usual. Alternatively the python packages index also contains official releases,the latest of which can be obtained by: easy_install milk or: pip install milk if you use these tools. Examples Here is how to test how well you can classify some features,labels data, measu
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GitHub - OlafenwaMoses/ImageAI: A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
GitHub - addyosmani/predictive-fetching: Improve performance by predictively fetching pages a user is likely to need
[PDF]Machine Learning for Systems and Systems for Machine Learning Jeff Dean Google Brain team
Chainer: A flexible framework for neural networks
GitHub - pavelgonchar/colornet: Neural Network to colorize grayscale images
ilastik - ilastik
mlpack - Home
https://mlpy.fbk.eu/