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You can watch a video of his achievements here. The social tipping product brings together and analyses the opinions of over 450,000 users worldwide across 40 different sports. Along with ensuring fair coverage of the gambling industry we highlight the great work of the Calvin Ayre Foundation. Commentsviews and opinions expressed are those of the author and do not necessarily reflect those of CalvinAyre.

We ended the month with a total profit of 126 points which means we are now back in the game with an overall profit of 28. We're back with another update to our Golf Betting Expert review and we've seen a slight increase in the strike rate this month, however it still ended with a loss in the end. We lost 19 points in total which gives us an overall loss of 97.

Since last month we noticed that the advised starting bank on the sales page has now been upped from 200 to 500 points, which seems a much more sensible size after witnessing the massive swing in variance the service has experienced over the last couple of months. We are going to continue following the service for another three months and will report back soon with our next update. It's been a turbulent time in our Golf Betting Expert review with a terrible losing run where just 2 out of 42 bets returned a profit.

After the bets from the Tour Championship and Portugal Masters had been settled, our 200 point bank had dwindled all the way down to 19. The next set of tips were received on the following Thursday ahead of the British Masters, but at this stage our bank was 0. Technically this is a bust bank, but we went on to record the available odds and waited to see what happened next anyway.

Since starting the review we are still down by 78. Clearly the advised starting bank of 200 points is not sufficient and we can't deny that we have lost confidence in the service.

Despite this, we have decided to continue following the tips for a little while longer to see whether a recovery can be made and whether the recommended bank will be adjusted. It's been a pretty awful start to our Golf Betting Expert review with a poor strike rate of 4. Just 3 bets from the 63 we received returned a profit which gives us an overall loss of 95. We did expect long losing runs as that goes hand in hand with golf betting, but we weren't expecting it to be this bad.

Hopefully we will see an improvement over the next month, otherwise this could turn out to be a disaster. We have also had trouble obtaining the advised odds for quite a lot of the selections, with our average odds being 57. This could be an issue as it will affect our bottom line in the long run.

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These are unavoidable when betting at high odds and we can see from the past results that strings of 15-20 losing bets or more are not uncommon. Selections are emailed out once per week on a Tuesday at around 11. Stakes are advised for each selection between 0. We will start with a three month review initially, but due to the nature of the service it's more than likely that this will run on for a longer period.

Advised OddsAvailable Odds Number of Bets3838 Total Stakes (pts)102.The differences are shown in the following table: Online prediction Batch prediction Optimized to minimize the latency of serving predictions. Optimized to handle a high volume of instances in a job and to run more complex models. Can process one or more instances per request. Predictions returned in the response message.

Predictions written to output files in a Cloud Storage location that you specify. Input data passed directly as a JSON string. Input data passed indirectly as one or more URIs of files in Cloud Storage locations. Returns as soon as possible.

Anyone with Viewer access to the project can request. Must be a project Editor to run. Runs on the runtime version and in the region selected when you deploy the model.

Can run in any available region, using any available runtime version. Though you should run with the defaults for deployed model versions. Runs models deployed to Cloud ML Engine. Runs models deployed to Cloud ML Engine or models stored in accessible Google Cloud Storage locations.

The needs of your application dictate the type of prediction you should use. 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.

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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.Please thank Erla for the terrific job she did in setting up our trip. I have already recommended your service to many of my friends. Our agent, Larus, was extremely helpful and quick to answer questions. We really appreciated the detailed itinerary with sight-seeing recommendations and highlighted route on the map.

It made for an easy, seamless experience. All of the hotels and guesthouses were amazing and had friendly staff.

We couldn't have picked better accommodations if we had tried to plan it on our own. Even the rental car company was easy to work with and helpful. I would highly recommend Nordic Visitor to family and friends. The accommodations booked were of excellent quality and very conveniently located to the train stations and the city's attractions.

The staff at every hotel was wonderful - very helpful, able to communicate in English. The trains and buses were punctual, clean and comfortable. A very positive experience. We had a wonderful trip. The highlights were definitely the Pulpit Rock an Kjerag mountain hikes. I would highly recommend them to your customers.

We recently spent a week in Iceland based in Reykjavik, including a three day self drive tour along the South coast fully arranged by the Nordic Visitor centre. The tour was well organised by the staff at Nordic Visitor Centre. Everything was easy and smooth. Our only regret is that we did not spend enough time in the country.

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There is so much more to see. We want to go back again for at least two weeks so we can tour the whole amazing country. We had taken 9 days group tour as a part our 25th Wedding anniversary celebration.Like many other forms of social media, online review sites give you the chance to develop a closer relationship with your customers.

You're likely to get to read reviews from a range of customers, many of whom might not otherwise tell you their opinions of your business. You can also reply to both positive and negative reviews, demonstrating that you're interested in what customers have to say. Through your replies, customers can get to know you as an individual, not just 'business x'. In fact, some review sites (e. Yelp) require business owners to post a clear personal photograph before they are allowed to respond to reviews.

Many customers enjoy knowing the person behind the business, and may become more loyal to you as a result. Phone scam reported from 'Business Queensland'General enquiries 13 QGOV (13 74 68) Skip to header Skip to content Skip to navigation Skip to footer Take survey At the end of your visit today, would you complete a short survey to help improve our services. When you're ready, just click "Start Survey".

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Yet a lifetime of experience, plus a quarter century of reading and reflection, has convinced me that it is a big waste of time and money. You want us to waste even more.

No man can serve two masters, the Bible teaches, but Mike Pence is giving it his all. To mark this historic civic occasion, the cavernous factory where the event is being held has been transformed. The cryptocurrency is almost certainly due for a major correction. But its long-term value remains a mystery. To call Bitcoin the biggest and most obvious bubble in modern history may be a disservice to its surreality.

The price of bitcoin has doubled four times this year. This astronomical trajectory might make sense for a new public company with accelerating profits. Bitcoin, however, has no profits. It is a digital encrypted currency running on a decentralized network of computers around the world.

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Ordinary currencies, like the U. Mike Pence was, by his own account, a terribly unpopular kid. Long before he became vice president of the United States, Pence was a total outcast. In the spring of 2007, I moved to New York City to cover what I was sure was the most important story in the country. One of those annoying people who had settled on a career before I knew how to drive, I was a young and enthusiastic reporter on the education beat. Both liked to say that their work, begun in 2003, was the next phase of the civil-rights movement.

Daniel Shaver was unarmed and begging for his life. This week, a jury found the police officer who killed him not guilty of murder or manslaughter. At the time, the man who shot him, former Officer Philip Brailsford, was on trial for second-degree murder, and body-cam footage of the killing had yet to be released. Now, that chilling, deeply disturbing video is available. The relevant portion begins at the 12 minute 50 second mark.Comparative Religion for Dummies.

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Nostradamus 2003-2025: A History of the Future. The World of Columbus. The End of the World: An Annotated Bibliography.

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World Religions in America: An Introduction. Apocalypse Delayed: The Story of Jehovah's Witnesses. University of Toronto Press. The Finished Mystery (Studies in the Scriptures). International Bible Students Association. The Mask of Nostradamus. Retrieved January 8, 2013. Millennium, Messiahs, and Mayhem: Contemporary Apocalyptic Movements. Century's End: An Orientation Manual Toward the Year 2000. The Restoration of Christianity. Eve of Destruction: Prophecies, Theories and Preparations for the End of the World.

Stamford, Connecticut: Longmeadow Press. End times: A Report on Future Survival. The Word For Today.

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Deadly Cults: The Crimes of True Believers. Reformation and Modern Rituals and Theologies of Baptism: From Luther to Contemporary Practices.

The End of the World. Expecting Armageddon: Essential Reading in Failed Prophecy.In addition, Jon led the North America media strategy and social media management teams. Before founding Tru Optik, Andre served as a Vice President of Investments at JP Morgan Chase and also led the Media and Entertainment division at a boutique investment bank in New York City.

Brian Wieser is senior analyst at Pivotal Research, where he covers advertising-related securities including media owners, agencies, data and marketing technology companies.

As an analyst, he has received awards from Institutional Investor and Reuters. Brian is also a CFA charterholder. Brett Wilson is VP, Adobe Advertising Cloud. Brett began his career at Accenture, where he led system implementations for Fortune 100 clients. He secured his MBA at the UC Berkeley Haas School of Business, where he and co-founder John Hughes won the UC Berkeley Business Plan Competition in 2007.

A frequent speaker at industry conferences, Brett has been featured in Advertising Age, The Wall Street Journal and The New York Times. Linda Yaccarino is Chairman, Advertising Sales and Client Partnerships, NBCUniversal.

She reports to Steve Burke, Chief Executive Officer, NBCUniversal.

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Since joining the company in 2011, Yaccarino has transformed NBCUniversal Advertising Sales. Prior to joining NBCUniversal, Yaccarino served as Executive Vice President and COO of Turner Entertainment Advertising Sales and Marketing and Acquisitions. Yaccarino sits on the boards of ascena retail group, Inc. Mark brings over 20 years of digital marketing leadership to his role as CEO of Telaria, Inc.

In March of 2015, Mark successfully led the sale of eXelate to the Nielsen Company, the global leader in measurement and analytics, where he became an EVP, launching and leading the Nielsen Marketing Cloud. Mark has been at the forefront of digital disruption since 1997 when he joined Modem Media Poppe Tyson, a pioneering digital ad agency and birthplace of the first banner ad.

John Ebbert is publisher of AdExchanger, an online trade publication he began in 2008. AdExchanger is devoted to the emerging trends in data-driven digital advertising and marketing and enables the exchange of ideas between all members of the ecosystem. James joined AdExchanger in March, 2015, after a recent stint in communications for advertising technology companies.

He spent two years in TV production, working for the NFL and then for the PBS NewsHour, where he covered the 2012 election and foreign affairs. At AdExchanger, he covers the ecommerce landscape, as well as innovations in digital marketing. Tilde Herrera is the opinions editor at AdExchanger, where she oversees the publication of all op-ed columns, including Data-Driven Thinking and Sell Sider.

Based in San Francisco, she has covered business, food and sustainability as a reporter and editor for a number of publications.

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Her work has appeared at the San Jose Mercury, San Francisco Chronicle, Associated Press, GreenBiz, Grist and KQED, among others. He often reports on issues surrounding data management as well as the confluence of media, creativity and technology. Prior to AdExchanger, he was senior editor at Direct Marketing News.

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He also spent three years as an analyst at Datamonitor, where he focused on customer interaction technologies (i. His articles about the traditional publishing industry occasionally show up in Publishers Weekly.

He is a writer, but he is not from Brooklyn.