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The phone was a great touch and very much appreciated. The tour was amazing and let me see Norway in a way that I had not imagined. The hotel personnel were very helpful, and the breakfasts were amazing. I thoroughly enjoyed the fjord tour from Flam to Gudvangen.

It was a great tour. From booking to the final date of the tour, everything was great. Thank you for an amazing experience. Cicci, was wonderful from the beginning, she was very patient with us while we made arrangements for our specialized tour. I felt taken care of at every stop. I know how much work it is to make arrangements so I really appreciated all her work.

Thank you Cicci for a trip of a lifetime. Excellent hotels, great location. Sirry was very helpful. Very informative, made it easy to do a self guided tour. We were very impressed with everything you did for us. All the arrangements worked as planned and the information you provided about the tour was excellent. We would have no hesitation in using Nordic Visitor again Hafdis was very professional and helpful throughout the process.

I am grateful to her and everyone else at Nordic Visitor for putting together this experience for my son and me. I feel like I could be the US spokesperson for travel and tourism in Iceland. Thank you for all that you did to make our trip truly incredible, memorable and wonderful. Wonderful, exceeded our expectations. We enjoyed touring at our pace and having highlights identified in advance. We supplemented with our own research.

We also enjoyed the thrill of being surprised by the quality and diversity of the hotels each night. The Guesthouse Sunna was great with excellent breakfast, a very nice apartment, perfect location, and great assistance from the service desk.

All of the tour buses picked us up and dropped us off right in front. The tours were superb. All of them stop for breaks and food several times throughout and the guides were talkative and knowledgeable. The food in Iceland is the best, by the way.

I have nothing but great memories of this trip and recommend Nordic Visitor to my friends without hesitation. Overall, this has been one of the top vacation experiences in my life. I felt that Solveig and Nordic Visitor took excellent care of me and my granddaughter and made our trip relaxing and enjoyable.

I could not have planned this so well. The reliability of tour guides, the drivers being on time when they were expected, and having someone available at Nordic Visitor when I needed to make a change was reassuring and so valuable.

We plan to call Nordic Visitor again within the next couple of years for a return trip. The map provided by Nordic Visitor was a fantastic resource. Then, our booked excursions and points of interest along the way were marked in orange, with written details added at the side. This made it easy for use to reach our excursions at the right times and directed us to great places for homemade ice-cream, lobster dinner, and scenic delights.

I can't say enough good things about our experience with Nordic Visitor. They thought of everything beforehand--as a result, I had a stress-free, fun-filled vacation with no negative surprises.Overall it was a wonderful family trip that we'll remember forever.

Aharon, Israel The Classic Fjords Route, June 2016 My wife and I thoroughly enjoyed our 11 day self-drive trip to Norway. We were very satisfied with the arrangements made by Nordic Visitor and we were happy that an experienced tour company planned our trip instead of us trying to plan it by ourselves. We really enjoyed Trondheim and we are happy that we decided to pick the self-drive tour that finished in Trondheim.

All the travel accommodations went like clockwork. Hotels were mostly quite easy to find and were comfortable, albeit somewhat marginally comfortable in a couple of cases. Again, I would like to compliment Sindre Matthiason. Kudos out to him. He was so very helpful and had everything well organized for us, which really helped to alleviate any anxiety we might have had initially.

We really loved Norway - Oslo, Bergen and all other stops. We also enjoyed Stockholm but found it to be just another big city - kind of like going to San Francisco, London or Berlin.

They all have much in common. Gary and Sandy, United States Iceland Full Circle, June 2016 I have put comments in TripAdvisor but again, Helga was terrific. Deirdre and Charlene, United States Express Iceland, June 2016 Had a great time at all hotels. Gerald and Carol, United States Express Iceland, May 2016 We loved your beautiful country and the wonderful scenery in every part. John and Linda, United States Iceland Full Circle - Winter, May 2016 We have traveled together for 42 years. Our Icelandic experience will be fondly remembered, it was very special.

We always felt welcome. We never had a bad meal. The scenery was no less than spectacular. Our thanks to everyone at Nordic Visitor. Michael, Canada Iceland Complete, May 2016 We were thrilled with the accommodations and really everything about the tour.

Janet, United States Highlights of Scandinavia by car, May 2016 We had a great time on our trip. Jim and Dale, Canada The Natural Wonders of Iceland, May 2016 The tour exceeded our expectations and without a doubt it was one of the greatest vacations we have ever taken. Julee and Matthew, United Kingdom Iceland Grand Tour, May 2016 Booking with Nordic Visitor was a wonderful experience. We absolutely love Iceland. The Iceland Grand Tour was well planned by Helga.

Perfect balance on the hotels. So much really useful information and tips on things not to miss. Really helped to take the stress out of the holiday with regards to booking the hotels and allowed us to focus on seeing the beautiful nature of Iceland.

Pam, Canada The Natural Wonders of Iceland, April 2016 Accommodation was better than expected and all the provided meals were top quality and representative of the country's cuisine.See what Feefo can do for you Industry-leading products Our award-winning platform comes with a suite of intuitive tools as standard. Smart Themes Power your review integration with machine learning. More Info SEO Audit Fine-tune your SEO strategy and navigate pitfalls, with an in-depth audit from one of our Feefo experts.

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See what Feefo can do for you More traffic Thanks to our partnership with Google, Yahoo and Bing, genuine reviews can drive traffic to your website. Increased sales Reviews boost sales. Valuable insights Our world-class analytics and reporting suite provides you with in-depth business insights. Trusted by the best. We only collect real reviews from real people, like you. Shall we get started. It is with a commitment to total transparency that we have chosen to offer you the opportunity to consult but also to place your review on this page.

A personal reply The hotel manager personally deals with customer feedback and strives to respond in a timely manner, whatever the nature.

A commitment at the heart of the New Hotel group. Do you want to check our latest offers to prepare better your journey. Don't hesitate to contact us for more information. Go to Setmore All Collections Booking Page Customer Reviews Customer Reviews Let customers rate and post reviews about the service they received Written by Cassandra Koehler Updated over a week ago Setmore's built-in customer review feature allows your customers to post reviews directly on your Booking Page.

Built-in moderation tools will also give you, the account holder, the power to approve or hide reviews as needed. Below we'll walk you through how to set up taking reviews on your Booking Page, as well as how customers can post a review.

Under where it says Your Booking Page, click the "Configure" button. In the Booking Page window, click the "Review" tab. Customer reviews are now enabled.Wisconsin and Illinois are very likely Democrats gains from Republicans in blue states. Nevada is now a tight hold for the Democrats. Indiana, Pennsylvania, New Hampshire, and Florid are all leaning Republican by a whisker.

Ohio and North Carolina are leaning Republican a little more strongly. The chart tracks the probability of victory on PredictWise since we started state-by-state predictions on February 27, 2016. I know that an efficient market should have everything priced in immediately, but the state-by-state predictions have slipped slightly above the national predictions in the last few days. She just needs to win one of those and she is president. At this point I have been constructing the predictions independently and they have stayed very consistent.

If this divergence continues I will become increasingly concerned about whether the national markets are suppressed. If there is a good lesson for American public opinion from Brexit it this. The two set of voters: leave and remain, live in a totally different reality. The remain voters got increasingly freaked out about the British economy as a possibility turned into a reality.

The leave voters, most of them, assume that it was meaningless fit of the elite bankers who were upset they did not get their way. A small fraction of leave voter regret their vote. But, remain would most likely win a re-vote, because a huge number of non-voters feel silly for not voting remain. Brexit happened, what does that mean for the USA. This does not affect how I predict the USA election, because (1) the USA has a long history of data versus a one-shot event (2) the USA has many outcomes to calibrate on versus just one outcome (3) we have more data for the USA election than Brexit.

But, we certainly learned that a segment of the UK voters really want immigration restrictions and trade barriers. And then there were two. While Bernie Sanders is technically still running, Donald Trump v. This lead may be surprisingly small to some people (Democrats) or surprisingly large to others (believers in fundamental models). A lot more to follow in the next 6 months and 4 days. It has been so much fun, but there is a really good chance that the primary effectively ends in 30 minutes feeling nostalgic yet.

A quick post on the state of the election at 191 until Election Day. Also, just added Newt Gingrich into the Republican VP slot should keep an eye on him. We pushed some updates to the site this morning. Musings will be brief updates on data, so I can reserve blog posts for more complete thoughts. Our polling reflects bleeding-edge research into cost-effective, fast, flexible, and accurate polling with an emphasis on politics and finance.

We infuse raw polling data with machine-learning-based post-polling analytics along with a host of other data. The backbone of predictions on this site are market-based, generated from real-money markets that trade contracts on upcoming events. PredictWise is run by David Rothschild an innovative, and stylish economist at Microsoft Research in New York City, but should in no way be construed as representing the views or predictions of Microsoft or any of its entities.

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How do these match. Prior to the end of the primary strategic or upset party voters will state they will not vote for the other possible nominees. That is helpful to their candidate. Clinton, but not vote or vote for Clinton v. Starting with the 2012 map, Clinton just needs to hold VA, OH, or FL. Pollster averages have her up by 12 pp in VA, 3 pp in OH, and 2 pp in FL. Real Clear has her up 13 pp in VA, 1. This tends to have some predictive power, in addition to polls, at this early point.The post at Northcutt is not the definitive way to rank for the rich answer box since we are dealing with Google algorithm here, after all.

Its algorithm can never be reduced to an exact science consider of how unstable it is. However, the post should give you a good idea of how you can increase your chances of getting your page on top the top of search results. Keep an eye on the Mozcast Google Feature review for other types of content that features within Google results.

Rich Answers are referenced here as 'featured snippets'. A similar feature is 'Related questions', showing how our articles should try to cover these questions. Images and videos are other better known ways of gaining cut-through in the SERPs for some search terms - check which are important for your industry.

Ever since, marketers have always speculated user engagement as a possible ranking factor. This covers the average time on site, bounce rate, pogo sticking, and others. For conversion, it is a proven factor that determines the effectiveness of page elements that contribute to the chances of visitors committing to your call to action. However, what makes this factors difficult to measure in search engines is the lack of data supporting it.

User engagement is too indirect an influence on search rankings. Nonetheless, it is something that all website owners need to optimize if they are serious about getting more out of their SEO efforts.

If the user finds the website beneficial, you can bet Google will as well. Heatmapping quickly comes to mind when thinking of user engagement. The idea here is that the more clicks a page accumulates from its links, the more interaction it has with users. Tools like SumoMe Heat Maps and CrazyEgg are great ways to break down the number of clicks made by users on your tracked site pages.

From here, you can see which links are clicked the most and least. You can then optimize your site by improving your CTA links and buttons based on the accumulated data. To analyze visitor engagement with your site pages, the SumoMe Content Analytics is an extremely helpful tool in looking how many of your site visitors scroll down until the very end of the page.

Determine which elements of your site pages serve as obstacles that prevent visitors from scrolling down your page and optimize your site as you see fit. The mobile market is big. So big, in fact, that Google is still figuring out how to provide mobile users with a better search experience. A faster loading site means more chances to retain visitors.

While there is also interest in spending on mobile ads as the figures from eMarketer show, Google will soon take a more crucial role in delivering content to mobile users, starting with app store optimization. Originally, apps are indexed on App Store and Google Play, not on Google search. Through App Index, apps are now indexed on Google search.

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The search ranking of apps falls under the App Pack or Deep Link category.Note: This document describes both batch prediction and online prediction. Online prediction is a Beta feature of Cloud ML Engine. It might be changed in backward-incompatible ways and is not subject to any SLA or deprecation policy. How it works The Cloud ML Engine prediction service manages computing resources in the cloud to run your models. Here is the process to get set up to make predictions in the cloud: You export your model using SavedModel as part of your training application.

Note: You can use batch prediction to get inferences for a SavedModel that isn't deployed to Cloud ML Engine. You format your input data for prediction and request either online prediction or batch prediction When you use online prediction, the service runs your saved model and returns the requested predictions as the response message for the call. Your model version is deployed in the region you specified when you created the model. Although it is not guaranteed, a model version that you use regularly is generally kept ready to run.

When you use batch prediction, the process is a little more involved: The prediction service allocates resources to run your job. The service restores your TensorFlow graph on each allocated node. The prediction service distributes your input data across the allocated nodes. Model deployment Cloud ML Engine can host your models so that you can get predictions from them in the cloud.

About models and versions Cloud ML Engine organizes your trained models using resources called models and versions.

What's in a version. Naming models and versions Model and version names must: Contain only (case-sensitive) mixed-case letters, numbers, and underscores. Begin with a letter. Contain 128 or fewer characters. Be unique within a given project (for models) or model (for versions). There are no rules for names beyond those technical requirements, but here are some best-practices: Model names should be descriptive and distinctiveyou may need to pick them out of lists of many names in logs or reports.

Version names are best kept short and simple. Model and version limits The Cloud ML Engine quota policy sets a limit of 100 models per project and limits the total number of versions (combined between all models) to 200. Model deployment parameters Cloud ML Engine needs some information to create your model version. Version name A name for the new version that is unique among the names of other versions of the model.

Description You can provide a description for your version. Deployment URI You must provide the URI of the Cloud Storage location where your SavedModel is stored. Cloud ML Engine pulls the model from this location and deploys it.

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This parameter is called --origin in the gcloud ml-engine versions create command. Runtime version Cloud ML Engine uses the latest stable runtime version to deploy your model version unless you specify a different supported one. The runtime version primarily determines the version of TensorFlow that the prediction service uses to run your model. When you run a batch prediction job you have the option of overriding the assigned runtime version.

Online prediction always uses the runtime version set when the model version is deployed. Manual scaling You can specify the number of training nodes to keep running for your model version. Warning: When you manually set the number of nodes to keep ready for your version, those nodes are considered to be constantly in use, even when not serving predictions.

This means that you are charged the hourly rate for each node from the moment you create the version until you delete it. You can't change this value without deploying your model to a different version.In a startup, technology is expensive and having a team to take care of that technology is even more expensive.

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To have all that taken care of with Ordering. It will take literally 3 min, just click here. Have the best day. I selected Ordering Co Initially because of their ability to work with the Goodcom Printers and their competitive price. I have stayed with them as they have been very helpful as my system grows. I currently have over 60 takeaways using the system and hope to have 100 by the end of the year.

All your demos makes it much easier to understand and implement. New features are added swiftly and you listen to your customers. Every member of the team is reliable, trustworthy and effective.

My business would not be moving in the right direction if it wasn't for Ordering Co. I love the flexibility of the software and its demonstrated ability to continually evolve and improve. There were several companies that I looked at that offered somewhat similar services, but after going through about four weeks of research, I could see that this companies' vision was bigger than where the other services were at.

My it guy at the time told me he saw potential in Ordering, but to go with someone more established, I told him that I believed in this company and that we could grow together. They also put a lot of effort in customer support and makes sure you get what you need in a short timeframe.

Which simply makes them the BEST. And many options for ordering food online. Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data. Populations can be diverse topics such as "all people living in a country" or "every atom composing a crystal". Statistics deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.

Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole. An experimental study involves taking measurements of the system under study, manipulating the system, and then taking additional measurements using the same procedure to determine if the manipulation has modified the values of the measurements.

In contrast, an observational study does not involve experimental manipulation. Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.

Inferences on mathematical statistics are made under the framework of probability theory, which deals with the analysis of random phenomena. A standard statistical procedure involves the test of the relationship between two statistical data sets, or a data set and synthetic data drawn from idealized model. A hypothesis is proposed for the statistical relationship between the two data sets, and this is compared as an alternative to an idealized null hypothesis of no relationship between two data sets.

Rejecting or disproving the null hypothesis is done using statistical tests that quantify the sense in which the null can be proven false, given the data that are used in the test. Working from a null hypothesis, two basic forms of error are recognized: Type I errors (null hypothesis is falsely rejected giving a "false positive") and Type II errors (null hypothesis fails to be rejected and an actual difference between populations is missed giving a "false negative").

Many of these errors are classified as random (noise) or systematic (bias), but other types of errors (e. The presence of missing data or censoring may result in biased estimates and specific techniques have been developed to address these problems.

Statistics can be said to have begun in ancient civilization, going back at least to the 5th century BC, but it was not until the 18th century that it started to draw more heavily from calculus and probability theory.

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While many scientific investigations make use of data, statistics is concerned with the use of data in the context of uncertainty and decision making in the face of uncertainty. Mathematical techniques used for this include mathematical analysis, linear algebra, stochastic analysis, differential equations, and measure-theoretic probability theory. Populations can be diverse topics such as "all persons living in a country" or "every atom composing a crystal".

Ideally, statisticians compile data about the entire population (an operation called census).