Yhat is a cloud solution for deploying predictive analytics at your company. Data scientists create pipelines to ingest and clean data and train and deploy models. Models are instantly accessible via REST, low latency streaming API, and batch mode.
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ŷhat | Blog | blog.yhathq.com Reviews
https://blog.yhathq.com
Yhat is a cloud solution for deploying predictive analytics at your company. Data scientists create pipelines to ingest and clean data and train and deploy models. Models are instantly accessible via REST, low latency streaming API, and batch mode.
Jessie Frazelle's Blog: Using an R Container for Analytical Models
https://blog.jessfraz.com/post/R-containers-for-data-science
Using an R Container for Analytical Models. Tuesday, June 30, 2015. So it turns out I’m pretty bad at vacation. I had this idea for a blog post and one thing lead to another and here we are…. You probably know by now I hate installing things on my host. At my previous job we did a lot of work with using Python and R for data science. I still love plotting data with ggplot and my favorite R package, wes anderson color palette. Here’s a fast intro into how to do this with an R Docker image. We need X11 for...
Data Science by Jenda R. Benetka | ZEEF
https://data-science.zeef.com/index
Jenda R. Benetka. Data Analysis, Machine Learning, Python, Visualization, Stats, Tutorials, Blogs, Algorithms, etc. In short, all the fun stuff in one place! Jenda R. Benetka. A Bohemian based in Norway interested in data science, cycling, traveling and photography. Jenda Rybák / rybak.io. Published 1 year ago. Updated 5 months ago. No free hunch - Kaggle Blog. Sebastian Raschka -Data science, ML, . KDnuggets - Latest News. Data Science Weekly Newsletter Archive. Data science @ Right Relevance. Webscope ...
Data Science Resources
http://www.dataschool.io/resources
Launch a data science career! Join my 17,500 YouTube subscribers. Here are a few of my favorite resources for learning data science and keeping up with the latest news:. Like Hacker News, but for data. R news and tutorials contributed by hundreds of bloggers. Lots of beginner-friendly content, usually in Python or R. Kaggle's competition and data science blog. From the Biostatistics professors that run Coursera's Data Science Specialization. Lots of short, timely posts. Python news and resources. Free PD...
Burn-in, and Other MCMC Folklore - Strong Inference
http://stronginference.com/burn-in-and-other-mcmc-folklore.html
Burn-in, and Other MCMC Folklore. Sat 09 August 2014. I have been slowly working my way through The Handbook of Markov Chain Monte Carlo. A compiled volume edited by Steve Brooks. That I picked up at last week's Joint Statistical Meetings. The first chapter is a primer on MCMC by Charles Geyer. In particular, he questions the utility of burn-in:. Burn-in is only one method, and not a particuarly good method, for finding a good starting point. This yields MAP estimates for all the parameters in the model,...
pymc - Strong Inference
http://stronginference.com/tag/pymc.html
Sun 30 November 2014. Calculating Bayes factors with PyMC. Statisticians are sometimes interested in comparing two (or more) models, with respect to their relative support by a particular dataset. This may be in order to select the best model to use for inference, or . Sat 09 August 2014. Burn-in, and Other MCMC Folklore. I have been slowly working my way through The Handbook of Markov Chain Monte Carlo. A compiled volume edited by Steve Brooks. That I picked up at last week's Joint Statistical Meetings .
Implementing Dirichlet processes for Bayesian semi-parametric models - Strong Inference
http://stronginference.com/implementing-dirichlet-processes-for-bayesian-semi-parametric-models.html
Implementing Dirichlet processes for Bayesian semi-parametric models. Fri 07 March 2014. Use of the term "non-parametric" in the context of Bayesian analysis is something of a misnomer. This is because the first and fundamental step in Bayesian modeling is to specify a. A useful non-parametric approach for modeling random effects is the Dirichlet process. We require two random samples to generate a DP. First, take a draw of values from the baseline distribution:. Theta 1, theta 2, ldots sim G 0 $. G(x) =...
Statistics - Strong Inference
http://stronginference.com/category/statistics.html
Posts categorized under: Statistics. Sun 30 November 2014. Calculating Bayes factors with PyMC. Statisticians are sometimes interested in comparing two (or more) models, with respect to their relative support by a particular dataset. This may be in order to select the best model to use for inference, or . Sat 09 August 2014. Burn-in, and Other MCMC Folklore. I have been slowly working my way through The Handbook of Markov Chain Monte Carlo. A compiled volume edited by Steve Brooks. Fri 07 March 2014.
ScienceCluster Overview · ScienceCluster
https://sciencebox.readme.io/docs/getting-started
Slug:getting-started,type:basic,title:ScienceCluster Overview}. Launching Editors / IDE's. Run or Schedule Jobs. Configuring ScienceCluster to Use a Spark Cluster. Running Interactive Spark Analysis in Jupyter. Running Standalone Spark Jobs in ScienceCluster. This page will help you get started with ScienceCluster. You'll be up and running in a jiffy!
Project Settings · ScienceCluster
https://sciencebox.readme.io/docs/project-options
Launching Editors / IDE's. Run or Schedule Jobs. Configuring ScienceCluster to Use a Spark Cluster. Running Interactive Spark Analysis in Jupyter. Running Standalone Spark Jobs in ScienceCluster.
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Yenihayat Bilişim Teknolojileri A.Ş.
Çoklu Kategorilerin olduğu bölüm. Epeyce hastaydım ve gün ışığı beni uyanmaya zorlamasına karşın yataktan çıkmaya hiç hevesli değildim. Uykumun arasında, yatağın konumu gereği. İnternet İnternet olalı, böyle data görmedi. Her şey pek güzel, internet icat olalı, dünya tepeden tırnağa değişti ve bu değişim hız kesmeden. Aynı fikirde olmamız gerekmediği konusunda hemfikiriz. İlk günler nasıl da şaşırtıcıydı değil mi? İçindeki karşı çıkma hissini -artık- bastıramayan ve sonrasında günlerce evinin. Anadolu Ün...
ŷhat | Blog
Machine learning, data science, engineering. The Code Behind Building a FiveThirtyEight post. Dissecting a FiveThirtyEight post on baseball payrolls and wins. Decision Making Under Uncertainty: An Introduction to Robust Optimization (Part 2). By Saba Neyshabouri Jul. Part 2 of an introduction to robust optimization and how to deal with uncertainty. Decision Making Under Uncertainty: An Introduction to Robust Optimization (Part 1). By Saba Neyshabouri Jul. By Eric Cox Jul. ROC Curves in Python and R.
(주)YH데이타베이스 :: (주)YH데이타베이스
전자정부 정보보호 솔루션페어 2018안내. 오는 3월 14일 16일까지 일산 킨텍스에서 개최되는. 전자정부 정보보호 솔루션페어 2018 (e-GISEC Fair 2018)"에. 정부부처 및 공공기관의 전자정부구축을 위한. 정보화 및 정보보호 솔루션, 모바일 전자정부솔루션 등. 빅데이터, 지능정보, 정보보안, 금융보안, 개인정보". 와 같은 다양한 보안 SW제품을. 한자리에서 체험 및 확인 하실수 있습니다. 여러분의 많은 관심과 참여 바랍니다. 일산 킨텍스 제 1전시장 4 5홀). 전시기간 : 2018.03.14(수) 2018.03.16(금). 무료 참가신청은 아래 링크를 클릭하세요! 전자정부 정보보호 솔루션페어 2018안내. 해커톤대회 and SW융합기업 홍보전시회 안내. E-GISEC 2017 전시회 후기. 전자정부 정보보호 솔루션페어2017 참가안내. YH데이타베이스에서는 어제 한해를 마무리하는 종무식을 가졌습니다. 경북대학교내에있는 "르네상스뷔페"에서 맛있는 시작으로. Html / css (5).
Yhehs Clothing Blog - YHEHS es una marca de ropa informal-casual orientada a los expertos, amantes y aficionados del motor sport para los que su pasión por el motor no es tan solo un trabajo o una afición sino un estilo de vida. YHEHS se inspira en la prec
BakuGP, el nuevo circuito de Europa. Bienvenid@s a BakuGP, el nuevo circuito de F1 urbano de Europa El circuito que está de estreno este año está en Azerbaijan, que, aunque no nos suene demasiado resulta que está en Europa. La república caucásica acoge por primera vez un… Leer más. CanadaGP, circuito de campeones. GRAN PREMIO GP 2016. Monaco GP, el circuito de las estrellas. GRAN PREMIO GP 2016. GRAN PREMIO GP 2015. GRAN PREMIO GP 2016. No hay ningún evento que mostrar. Circuito de Albert Park.
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The YellowHammer Blog
The infrequently-updated YHMG blog. Like What You See? Monday, June 2, 2014. RTB 20: Real-Time Bathroom Updates. At YellowHammer HQ, we’ve been hard at work trying to figure out how to improve our RTB systems. Last quarter, management gave our engineers a directive: use our internal data and insights to take RTB to the next level for our internal teams. Unfortunately, we should have specified that RTB stands for. We are not kidding. If all of this sounds very complex, that’s because it is. Now ...Possibl...
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