Have you ever been writing a post with the help of someone who does not have access to your blog and needed to give them the ability to preview it before publishing. This plugin takes care of that by generating an URL with an expiring nonce that can be given out for public preview. Previously this plugin was maintained by Matt Martz and was an idea of Jonathan Dingman.
Thanks to Hans Dinkelberg for his photo. The plugin generates an URL with an expiring nonce.
After 48 hours the link is expired and you need to copy and share a new link which is automatically generated on the same place under the editor. As a content generator writing and editing content for clients, this plugin has been a fantastic time saver in allowing me to share draft posts without asking clients to login to their sites. Please revert to the original EN title if possible. Very useful tool to share previews with others (without login).
Generated links are valid for 48 hours which can be changed and extended easily. Translate into your language 1 out of 3 View support forum WordPress. Usage To enable a public post preview check the box below the edit post box. The link will be displayed if the checkbox is checked, just copy and share the link with your friends. To disable a preview just uncheck the box. The checkbox is only available for non-published posts and once a post was saved as a draft.
Can I extend the nonce time. Work like a charm. Single purpose, easy to use plugin Easy to install and use to provide access to an unpublished post. Works fine Good product and works fine. Thanks, Easy to use, does what it should Very useful tool to share previews with others (without login). Send no-cache headers for public post previews. Remove preview status from posts which are trashed or after scheduled posts are published.
Add support for paged posts. With the filter you can adjust the preview link. Through a change in 2. With the filter you can adjust the expiration of a link.Is something important missing. Become a WordReference Supporter to view the site ad-free. Chrome users: Use search shortcuts for the fastest search of WordReference.
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To use our site as it is intended, you will need to download a newer browser. The browsers we support are: Internet Explorer 8 Internet Explorer 9 Internet Explorer 10 Firefox Chrome Safari Betting on auto racing has exploded in popularity in Vegas in recent years, and its appeal continues to grow.
The structure of betting on auto racing is similar to that of golf. The most basic wager involves picking the winner of a race. Typically a sports book will list 20 or more individual drivers along with a field (all others) option, at various odds. For example, Jeff Gordon may be listed at 4-1, Jeff Burton at 15-1, Casey Atwood at 100-1, etc.
Auto racing matchup propositions also are available, in which two drivers are paired against each other in a head-to-head wager, with a betting line on each driver set by the oddsmaker. The driver with the better finish in the race wins the matchup. To bet on baseball, tell the ticket writer the bet number of the team you wish to bet and the amount you wish to wager. If your team wins the game, you win.
The payout varies according to the odds posted. Baseball odds are shown using a "Money Line. A "minus" (-) preceding the number indicates the team is a favorite. You can arrive at the underdog's price by looking at the favorite's line.
Dime lines are slowly disappearing as sports books look to make a larger profit during what is traditionally the slowest betting season. Several books still offer dime lines. Money lines change constantly.Your breath is a powerful and simple way to anchor yourself in the present moment. Whenever you are having a hard time staying in the now, take deep breaths, and focus on your breathing.
You could even count your breaths. Something I like to do is count to four on the inhale and four on the exhale. It focuses the logical part of my brain on counting and allows me to focus on my breath. After a while I can release the crutch of counting and just be. In fact, they are rarely right, especially if they make you feel bad.
Question your thoughts constantly. When you start to feel negative emotions, use it as a reminder to examine what thoughts are causing the commotion. Most people walk around all day letting negative thoughts cause negative feelings.
We both know that nothing good can come out of this. It takes discipline to be mindful, but the rewards are peace and happiness. Even researchers are discovering the power of emotions.
Negative emotions not only have the power to make you feel bad, but can affect your physical health as well.
Another great way to stay anchored in the now is to use reminders. It can be as simple as tying a white string around your wrist. Each time you look at the white string, you are reminded of the present moment. Are you in the now, or are you somewhere else. There are no limits to what you can use as a reminder. If you want to take this even further, you can add a new reminder each week.Batch prediction latency If you use a simple model and a small set of input instances, you'll find that there is a considerable difference between how long it takes to finish identical prediction requests using online versus batch prediction.
Understanding prediction nodes and resource allocation Cloud ML Engine measures the amount of processing you consume for prediction in node hours. Node allocation for batch prediction The batch prediction service scales the number of nodes it uses to minimize the amount of elapsed time your job takes.
To do that, the service: Allocates some nodes to handle your job when you start it. Scales the number of nodes during the job in an attempt to optimize efficiency. Shuts down the nodes as soon as your job is done. Node allocation for online prediction The online prediction service scales the number of nodes it uses to maximize the number of requests it can handle without introducing too much latency.
To do that, the service: Allocates some nodes the first time you request predictions after a long pause in requests. Scales the number of nodes in response to request traffic, adding nodes when traffic increases, and removing them when there are fewer requests. Limitations of automatic scaling Cloud ML Engine automatic scaling for online prediction can help you serve varying rates of prediction requests while minimizing costs. Using manual scaling You can affect the scaling of online prediction for a model version by specifying a number of nodes to keep running regardless of traffic.
Prediction input data The data you use for getting predictions is new data that takes the same form as the data you used for training. These formats are summarized in the following table, and described in more detail in the sections below: Prediction type and interface Supported input format Batch with API call Text file with JSON instance strings or TFRecords file (may be compressed) Batch with gcloud tool Text file with JSON instance strings or TFRecords file (may be compressed) Online with API call JSON request message Online with gcloud tool Text file with JSON instance strings or CSV file Instances JSON strings The basic format for both online and batch prediction is a list of instance data tensors.
Individual values in an instance object can be strings, numbers, or lists. The following special formatting is required: Your encoded string must be formatted as a JSON object with a single key named b64. Online prediction input data You pass input instances for online prediction as the message body for the predict request.
Batch prediction input data You provide input data for batch prediction in one or more text files containing rows of JSON instance data as described above. Runtime versions As new versions of Cloud ML Engine are released, it is possible that models developed against older versions will become obsolete. Runtime versions and predictions You can specify a supported Cloud ML Engine runtime version when you create a model version.
Regions and predictions Google Cloud Platform uses zones and regions to define the geographic locations of physical computing resources. Prediction logging Batch prediction generates job logs that you can view on Stackdriver Logging. Getting predictions from undeployed models You can request batch prediction using a model that you haven't deployed to the Cloud ML Engine service.
Model testing You can use the Cloud ML Engine prediction service to host your models that are in production, but you can also use it to test your models. What's next Infer values from new data instances with online prediction. Home of the national championship game, finalists for some of the more prominent national honors were at the College Football Hall of Fame for the annual awards show.
We took the opportunity to poll as many of these college stars about their picks for the playoff. Two abstained citing a lack of overall knowledge while 11 gave their view of this four-team field. Alabama faces top-ranked Clemson in the Sugar Bowl after Georgia and Oklahoma meet in the Rose Bowl on New Year's Day. The most popular pick: Clemson. The Tigers got five votes, followed by Georgia's 3. This wasn't a scientific poll with equal representation from all geographic areas.
Just a few different views from some of the best players in the country. Oklahoma has just as good of a chance because it's different schemes.Flatline performs type inference, and will in general figure out the proper optype for the generated fields, which are subsequently summarized by the dataset creation process, reaching then their final datatype (just as with a regular dataset created from a datasource).
In case you need to fine-tune Flatline's inferences, you can provide an optype (or optypes) key and value in the corresponding output field entry (together with generator and names), but in general this shouldn't be needed.
Samples Last Updated: Monday, 2017-10-30 10:31 A sample provides fast-access to the raw data of a dataset on an on-demand basis. When a new sample is requested, a copy of the dataset is stored in a special format in an in-memory cache. Multiple and different samples of the data can then be extracted using HTTPS parameterized requests by sampling sizes and simple query string filters.
That is to say, a sample will be available as long as GETs are requested within periods smaller than a pre-established TTL (Time to Live). The expiration timer of a sample is reset every time a new GET is received. If requested, a sample can also perform linear regression and compute Pearson's and Spearman's correlations for either one numeric field against all other numeric fields or between two specific numeric fields.
You can also list all of your samples. You can also use curl to customize a new sample with a name. Once a sample has been successfully created it will have the following properties. Through the status field in the sample you can determine when the sample has been fully processed and ready to be used. Thus when retrieving a sample, it's possible to specify that only a subset of fields be retrieved, by using any combination of the following parameters in the query string (unrecognized parameters are ignored): Fields Filter Parameters Parameter TypeDescription fields optional Comma-separated list A comma-separated list of field IDs to retrieve.
A sample might be composed of thousands or even millions of rows. Thus when retrieving a sample, it's possible to specify that only a subset of rows be retrieved, by using any combination of the following parameters in the query string (unrecognized parameters are ignored).
BigML will never return more than 1000 rows in the same response. However, you can send additional request to get different random samples. Filtering Rows from a Sample Parameters Parameter TypeDescription. As with inclusion, it's possible to include or exclude the boundaries of the specified interval using square or round brackets Example: ". One of the limits can be omitted. This can be useful, for instance, when you're performing various GET requests and want to compute the union of the returned regions.
You'll want this only when unique is set to true, otherwise all those extra values will be equal to 1.Stephen is the principal owner and operator of Free Tours by Foot, a pioneering company offering pay-what-you-wish sightseeing tours.
In this article I have targeted the top six ways to go discount shopping in New York. So keep in mind, when it comes to purchasing clothing, everyone is picky about their wardrobe and how they acquire it. Outlet Shopping: (Read our full blog post) Arguably the most famous method for discount shopping in New York. There are many outlet malls outside of the city for all kinds of shopping.
The most popular outlet mall is Woodbury Common Premium Outlets in Central Valley, NY. In addition to Woodbury, check out additional outlet malls in New York, New Jersey and Pennsylvania at Outlettable.
Tips: Plan on spending a full day and if your going to shop a lot, consider hiring a private driver. There are several providers that offer to drive there, e. CitySights, who also offers a tourist shopping pass. Sample Sales: New York City is the only city where a designer can create, select fabric, manufacture, watch over production and sell their product without leaving the island.
Sample sales are the way to go for deals, even when shopping for national brands that are produced overseas. Design houses will rent different venues in Manhattan to liquidate their samples, over-runs and sometimes flawed pieces at a fraction of the retail price.
No returns be absolutely sure that you want the item. If you live in the area be sure to get on their email list you will be notified of the next designer sale in their venue. Never miss another sample sale, sign up with your email at www. If you like to shop the quaint boutiques, expect them to have sales only twice a year. Small shops are more careful about purchases and production.
Some continually producing small runs throughout the year and others but only twice a year. Larger retailers have sales more often. Find retail sale listings at www. Discount Department Stores: Century 21 is the most popular discount department store in New York City, known for its vast daily deals from shoes to sheets. Discount department stores are likely the most effective way to find cheap shopping in New York City.
With others the clothing is freshly cleaned, and ready to wear. Tip: Know the value of the label before you buy. Always check your garment for flaws and ask the store clerk about the return policy.
There are so many wonderful second-hand thrift shops in the city, from charity shops to independent second-hand stores. New York has the best second-hand stores because it is a well-to-do city with New Yorkers who love donating to a good cause. You can find many better thrift and vintage shops on www.
Many items are brand new and are donated by businesses and local designers.As someone who has been to Iceland many, many time (mainly for work) it is great to see how a local firm can be so much better than booking anything else. Usually I do self booking for everything, however I was finding great difficulty putting together a trip where all the hotels have availability for the dates we wanted.
My wife found Nordic Visitor and we contacted them. The request was something along the lines of "we want the full circle, however we want to do it in reverse, and we want to specifically at this hotel, etc. Within 10 days they (Alexandra) had managed to do everything we wanted and the price was very reasonable (Iceland has never been cheap, but it more affordable now than it was 20 years ago when I first started going there).
Everything from the initial pick up at the airport, through to hire car, hotel bookings, literally everything ran smoothly without any problems whatsoever. During the planning stages, Kolbrun was extremely helpful, answering all of our questions by email quickly and fully. The fjord region is absolutely beautiful and I think it important to actually drive the region to really appreciate it. Again, we always knew that Kolbrun was there to help us if we needed it and we thank you for her services.
Exceptional service from Nordic Visitor from start to end. Had a fantastic time in Iceland and can't wait to be back. All of the hotels were very nice. Rooms were adequate and clean. Breakfast was served at every hotel, which was very nice. Probably the best thing I've ever done. Amazing feeling being up on the glacier. Incidentally, we mistakenly took the closed road to get to the tour, got stuck in snow, and the Tour Guide pulled us out and escorted us to where we should have been.
Jelena was fantastic to work with. We had a lot of communication prior to the trip, she was very responsive to my questions and requests. We were able to book everything as we wanted it -- and during the trip we decided to change a few of our hotel stays and that was no problem at all. I loved the flexibility of the trip and the self-drive aspect.
We were able to enjoy a trip of a lifetime with no worries. Everything was taken care of for us. Iceland is a mysterious and beautiful country -- nothing like I've ever seen before. I loved every minute of my trip. Thank you for allowing us to enjoy the country in this way. We had a great time. He answered all of our questions in detail in a very timely manner.
We really appreciated the welcome packet: the bound book was fantastic. The (very) large map with our highlighted route and guesthouses was super useful. Everything that you did took away the stress of planning a vacation in a country where we didn't read the language :) It left more time for us to enjoy the scenery. As I think I have already said I very much appreciated the expertise and personalized service and would not hesitate to refer anyone I know to use your service.
I found Nordic Visitor superb to work with. Emails were answered in a timely fashion, information was presented in a clear and concise manner and Larus was fantastic to work with. Booking and payment was done smoothly all online and very reasonably priced.