DeepMind moves to TensorFlow
Posted by Koray Kavukcuoglu, Research Scientist, Google DeepMind At DeepMind, we conduct state-of-the-art research on a wide range of algorithms, from deep learning and reinforcement learning to systems neuroscience, towards the goal of building Artificial General Intelligence. A key factor in facilitating rapid progress is the software environment used for research. For nearly four years, the ope
Azure AI Vision with OCR and AI | Microsoft Azure
Explore Azure Get to know Azure Discover secure, future-ready cloud solutions—on-premises, hybrid, multicloud, or at the edge Global infrastructure Learn about sustainable, trusted cloud infrastructure with more regions than any other provider Cloud economics Build your business case for the cloud with key financial and technical guidance from Azure Customer enablement Plan a clear path forward fo
ŷhat | Rodeo: A data science IDE for Python
Today we're excited to introduce a new project: Rodeo. Rodeo is an IDE that's built expressly for doing data science in Python. Think of it as a light weight alternative to the IPython Notebook. We've been using it for projects internally, but today we're releasing it to the public! We hope you like it as much as we do. Why we built it I like the IPython Notebook for presentations and tutorials, b
Nonparametric Bayes Tutorial
Machine Learning Summer School 2012 Bayesian nonparametrics. P Orbanz. Machine Learning Summer School, 2012. [Videolectures] [Slides] Lecture 1: Clustering, Dirichlet processes, IBPs [Slides] Lecture 2: Gaussian processes, model construction, exchangeability, asymptotics Machine Learning Summer School 2009 At MLSS 2009, I gave two talks on the basics of measure theory and stochastic process concep
Portfolio
Introduction Approximately 25 years of experience Passionate about data privacy and censorship resistance Lead a team of ~30 engineers from hiring to delivering the product to the first customer. Worked in following projects / companies Ethereum Foundation ( worked on Swarm when it was part of Ethereum geth code) Swarm Foundation Prysmatic Labs (worked on PoS Merge) Shardeum Foundation (worked on
実践 遺伝的アルゴリズム
本書は、人工知能の技術の1つである遺伝的アルゴリズムを用いて、「ナンバーエリア」または「四角に切れ」と呼ばれる、数字だけではなく長方形という図形的な要素が入ったパズルの問題の自動生成について説明します。 理論の説明は最小限にし、実装を詳細に説明。後半ではパズル作家が問題を作る際に考慮するような、パズル問題として差をつける特長をプログラムに組み込むことも説明します。本書でナンバーエリアに挑戦することで、さまざまなパズル生成への応用力が身につき、パズル以外への適用も可能になるでしょう。 なお、本書はEbook版のみの販売です。 まえがき はじめに 本書の表記 サンプルコードの使用について 意見と質問 導入部 遺伝的アルゴリズムとは 巡回セールスマン問題への適応例 1章 遺伝的アルゴリズムとは 最適化問題 遺伝的アルゴリズム 2章 巡回セールス問題への適用 巡回セールスマン問題 GUIプログラム
Build a SPAM filter with R - ThinkToStart
You can find the complete code on github: https://github.com/JulianHill/R-Tutorials/blob/master/spam_class_r.r Introduction: The topic Machine Learning gets more and more important. The number of data sources grows everyday and it makes it hard to get insights out of this huge amount of data. This increases the need for machine learning algorithms. Our example focuses on building a spam detection
Accelerate Machine Learning with the cuDNN Deep Neural Network Library | NVIDIA Technical Blog
Accelerate Machine Learning with the cuDNN Deep Neural Network Library Machine Learning (ML) has its origins in the field of Artificial Intelligence, which started out decades ago with the lofty goals of creating a computer that could do any work a human can do. While attaining that goal still appears to be in the distant future, many useful tools have been developed and successfully applied to a
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Machine Learning Projects for .NET Developers
ICML Lille
http://www-labs.iro.umontreal.ca/~bengioy/dlbook/
GitHub - bigmlcom/BigMLKit: Marrying Machine Learning with Apple's ResearchKit/HealthKit.
Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.
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