TFX: A TensorFlow-Based Production-Scale Machine Learning Platform
TFX: A TensorFlow-Based Production-Scale Machine Learning Platform Denis Baylor, Eric Breck, Heng-Tze Cheng, Noah Fiedel, Chuan Yu Foo, Zakaria Haque, Salem Haykal, Mustafa Ispir, Vihan Jain, Levent Koc, Chiu Yuen Koo, Lukasz Lew, Clemens Mewald, Akshay Naresh Modi, Neoklis Polyzotis, Sukriti Ramesh, Sudip Roy, Steven Euijong Whang, Martin Wicke, Jarek Wilkiewicz, Xin Zhang, Martin Zinkevich Googl
Google の機械学習研究者による研究・エンジニアリングの進め方のメモ - MyEnigma
TensorFlowではじめるDeepLearning実装入門 (impress top gear)posted with カエレバ新村 拓也 インプレス 2018-02-16 Amazonで検索楽天市場で検索Yahooショッピングで検索 目次 目次 はじめに メモ 参考資料 MyEnigma Supporters はじめに Goolgleのベイズ統計、機械学習の研究者である Dustin Tran氏が下記のような面白いブログ記事を上げていたので、 そのメモです。 dustintran.com メモ Googleの機械学習エンジニアにによるエンジニアリングのやり方。研究に使うツールを紹介していて面白い。 https://t.co/IrPU3t34Wx— Atsushi Sakai (@Atsushi_twi) 2018年3月11日 ちょっと内容をメモしてみる。まず初めに何を解くべきかを考え
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
While great strides have been made in using deep learning algorithms to solve supervised learning tasks, the problem of unsupervised learning - leveraging unlabeled examples to learn about the structure of a domain - remains a difficult unsolved challenge. Here, we explore prediction of future frames in a video sequence as an unsupervised learning rule for learning about the structure of the visua
An Analysis of Deep Neural Network Models for Practical Applications
Since the emergence of Deep Neural Networks (DNNs) as a prominent technique in the field of computer vision, the ImageNet classification challenge has played a major role in advancing the state-of-the-art. While accuracy figures have steadily increased, the resource utilisation of winning models has not been properly taken into account. In this work, we present a comprehensive analysis of importan
Toward ethical, transparent and fair AI/ML: a critical reading list
**stopped maintaining in 2019 In the past 5 years there’s been a lot of enthusiasm about AI and specifically machine learning and deep learning. As we continuously deploy AI models in the wild we are forced to re-examine what are the effects of knowledge symbolisation, generalisation and classification on the historical, political and social conditions of human life. We also need to remind ourselv
jingwan-lu
Jingwan joined Adobe Research in 2014. She is currently leading a team of research scientists and engineers with the vision to disrupt visual content creation with big data and generative AI. Her research interests include generative image modeling (GANs, etc.), computational photography, digital human and data-driven artistic content creation. She has over 30 issued patents and over 40 publicatio
Deep Learningと自然言語処理
NIPS2013読み会: Distributed Representations of Words and Phrases and their Compo...Yuya Unno
Home Page of Geoffrey Hinton
Information for prospective students, postdocs and visitors: I will not be taking any more students, postdocs or visitors. Basic papers on deep learning LeCun, Y., Bengio, Y. and Hinton, G. E. (2015) Deep Learning Nature, Vol. 521, pp 436-444. [pdf] Hinton, G. E., Osindero, S. and Teh, Y. (2006) A fast learning algorithm for deep belief nets. Neural Computation, 18, pp 1527-1554. [pdf] Movies of t
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