New Yandex Service Uses Machine Learning for Hyperlocal Weather Forecast
26 November, 2015
Machine learning is Yandex's core technology. We’ve long been using it in almost all of our services — to answer users’ search queries, for machine translation, ad targeting, personal recommendations, and plotting routes on maps, among others. Since last year, our MatrixNet machine learning algorithm has been utilised for the optimisation of business processes in real enterprises — weopened Yandex Data Factory for this purpose.
Today we announce yet another application of machine learning in a new field for us — weather forecasting. For this we have developed our own forecasting technology Meteum, which will now be used in the web service and mobile application Yandex.Weather available for iOS and Android.
Basic weather forecasts are traditionally constructed using the Navier-Stokes equations. Models for describing weather are extremely complex, as they depend on a multitude of factors. Programs for their calculation consist of hundreds of thousands of lines of code and run on huge supercomputers. Nonetheless, they still make mistakes, so their forecasts need to be fine-tuned. Besides that, the complexity and resource-intensiveness of traditional calculations results in a situation where forecasts are made for relatively large regions and cities. Constructing a precise forecast for, say, a small village would require taking into account a large number of local factors – such as, solar radiation, phase transitions of water vapour, or thermal radiation from the soil. Performing this task using traditional methods is not much less resource-intensive than for a large city, while the number of people using such a forecast is much lower.
Using machine learning allows collating a large volume of historical data about forecasts and actual weather, identifying causality in forecasting errors and correcting them. This is quicker and easier, as it doesn’t require factoring in laws of nature for each new forecast, but simply corrects traditional mathematical models and localises the forecast down to specific latitude and longitude. That’s exactly what Meteum does.
Our new technology uses traditional meteo models to process the initial data, and works with intermediate results using Yandex’s machine learning technology MatrixNet. To calculate the weather, Meteum constantly compares forecast with actual weather conditions — more than 140,000 times a day. To learn about current weather conditions, we use meteorological station data, as well as weather information from other sources indirectly indicating the situation — about 9 terabytes of data every day. One of the sources is our users, who can let us know about discrepancies between forecasts and real weather conditions via the app. The more data we receive from them, the more precise Meteum’s forecasts will become.
Meteum currently works in 36 regions of Russia, with a possibility to expand to other regions or countries.
Yandex Chat Bots for Telegram Messenger
27 October, 2015
Our job is to make life easier for everyone, which sometimes means just showing them the opportunities they have never thought of before. We are always on the lookout for new possibilities for our users on any platforms or devices.
When Telegram instant messaging service launched its open Bot Platform last June, the new possibilities came up in the form of fun and efficient chat bots easily implementable on the service. When chatting to someone online it's much easier to just ask a chat bot a straightforward question and receive an instant answer without leaving the chat, than going over to the browser window and looking for information. Chat bots are good at providing simple, factual information, such as a weather forecast for the coming weekend, current traffic conditions, or definition for a new word.
To help chatters enjoy their chatting even more, some of our developers have made chat bots based on Yandex services using Telegram Bot API. Most of these chat bots provide information relevant for our users in Russia, Ukraine, Belarus, Turkey and Kazakhstan, but the ImageSearch chat bot and the Yandex Translator bot could be of use to anyone outside of our current key markets.
ImageSearch instantly offers the user a graphic image or photograph from the Yandex.Images service in response to a keyword request on Telegram. Just type what you want to see and ImageSearch retrieves a picture, which can be shared with other chatters in a couple of clicks.To see something else in response to the same request, just type “/more”. Add the ImageSearch bot to your chat and communicate with your friends using pictures, gifs or memes mined from the internet by the chat bot.
Telegram's stores currently offers over thousands of chat bot programs for every taste or any problem. To help other chat bot developers, whose goal to make life easier and more fun for everyone we share, we have created a free analytics tool, Botan. Based on Yandex’s free app tracking and analytics tool, AppMetrica, Botan allows chat bot developers know their audience better, including gathering information about specific audience segments or learning about which bot commands are the most popular with certain groups of people.
The New Mobile Analytics and Tracking: Real Time, All in One, Free for All
25 August, 2015
Yandex is rolling out a revamped version of its mobile app analytics platform – now under the name “AppMetrica”. The new platform features a powerful mobile ad tracking solution in addition to the pre-existing features – user analytics and crash reports. Now AppMetrica covers all key domains for marketers, publishers and developers – and they can access it completely for free and without any limits, in real-time mode and with a single SDK.
We released our analytics tool for the first time almost two years ago as Yandex.Metrica for Apps. It was our response to the lack of good user analytics solutions on market – we had to create our own to learn how mobile apps published by Yandex were performing. Then we thought it may be of interest to other people around the world, and opened it up for everyone – for free.
Since 2013 we’ve been getting requests from marketers and developers who love the way we do it – currently AppMetrica processes nearly one billion in-app events every day for apps connected to the service. However, users need more, and we got clear signals from our in-house mobile marketers who track Yandex’s app user acquisitions. The main problem is that they had to spend up to 15% of their budgets on mobile ad measurement tools alone, which is quite a lot even for us ☺. Another issue is that product analysts and managers couldn’t easily use detailed traffic source segmentation in analytics tools as the two are separated and usually developed by different providers. In the end, different tools require the integration of multiple SDKs, so project teams need to spend more time on development and testing. We spent almost two years solving these issues to turn AppMetrica into a fully-fledged, integrated, professional mobile analytics and tracking platform.
The new AppMetrica provides detailed ad campaign reporting. Users can drill down to analyse how well different creatives and ad placements are performing, see tracking link parameters breakdowns, and get user engagement reports by applying cohort analysis with retention and event conversion rates which gives a really insightful analysis of traffic quality. AppMetrica is integrated with the most popular mobile ad networks out of the box, including AdColony, InMobi, Millennial Media, Vungle, and many others. We keep expanding the list of ad networks, and users can also manually integrate traffic sources they need and set up postbacks in a few easy steps.
The new platform aids re-engagement improvements using state-of-the-art deep linking technology. Hardcore marketers have the opportunity to pull raw data from AppMetrica via its API so they can create in-house custom reports or use it in their proprietary software. They soon will get even more options to improve conversion: we are now working on integration with data export from AppMetrica to popular re-targeting and look-alike platforms.
AppMetrica works with Android, iOS and Windows Phone apps. Game developers will also enjoy our Unity plugin. AppMetrica is available for free and starts to provide reports in just a few minutes after rolling up an app with the integrated SDK.
Yandex Rolls Out Multifunctional App for Android Users in Russia
6 August, 2015
With more than 85% of the smartphone market in Russia, Android continues to be the country’s favourite operating system. The great variety of devices within a $200 price range supporting this platform, among other things, has contributed to Android’s popularity with Russians who are happy to compromise some of their smartphone’s technical quality, such as memory space, for its affordability. ‘There’s an app for that’ doesn’t really do it for a lot of budget smartphone users.
To make life easier for the owners of budget Android-based devices we have offered them an all-in-one application for their everyday needs – from current weather, currency exchange rates or traffic conditions to what’s on in the cinema around the corner or the shortest way to the nearest bank or restaurant. We have reissued our search app for Android to provide our users with a one-tap access to our key services on their mobile devices.
The new Yandex app has expanded its functions beyond search to include quick access to email, news, maps, city navigation, taxi booking, or any other service available in Yandex’s product range. To use any of these services one doesn’t even need to have a corresponding app on their phone – the refurbished search app will take them to the mobile version of the service at Yandex.ru. The new Yandex app allows the owners of low-budget Android-based smartphones to enjoy the full mobile experience without having to compromise anything.
First announced in 2011, the Yandex search app now has a weekly user audience of over three million. The new app can be downloaded from Google Play. The users of Yandex.Search in Russia, Ukraine, Belarus and Kazakhstan will be upgraded to the new Yandex app when they update their current version.
Now We’re Looking for Lepton Flavour Violation
21 July, 2015
Wouldn’t we all like to think that the world that we’re living in is more or less stable? Isn’t there a certain pleasure to be sure that our feet will be pulled to the ground as firmly tomorrow as they are today? Isn’t it reassuring to know that the cup of tea we’ve just put on our desk won’t disappear instantly and reappear on the bottom of the sea on the other side of the planet having traveled its diameter on a straight line? In classical physics, Newton’s laws give us this reassurance. These laws bestow predictability on objects or events as they exist or happen in our reality - on a macroscopic level. On a microscopic level - in particle physics - Fermi’s interaction theory, for instance, postulates that the laws of physics remain the same even after a particle undergoes substantial transformation.
In 1964, however, it became apparent that this isn’t always the case. James Cronin and Val Fitch showed, by examining the decay of subatomic particles called kaons, that a reaction run in reverse does not necessarily retrace the path of the original reaction. This discovery opened a pathway to the theory of electroweak interaction, which in turn gave rise to the theory we all now know as the Standard Model of particle physics.
Although the Standard Model is currently the most convenient paradigm to live with, it doesn’t explain a number of problems, including gravity or dark matter. Other theories compete very actively for the leading role in describing the laws of nature in the most accurate and comprehensive way. To succeed, they have to provide evidence of something that happens outside the limitations of the Standard Model. A promising area to look for this kind of evidence is the decay of a charged lepton (tau lepton) into three lighter leptons (muons), which happen to have a certain characteristic - flavour - that is different from the same characteristic of their ‘mother’ particle. According to the Standard Model, the probability of this decay is vanishingly low, but it can be much higher in other theories.
One experiment at CERN, LHCb, aims at finding this τ → 3μ decay. How are they going to find it? By searching for statistically significant anomalies in an unthinkably large amount of data. How can they find statistically significant anomalies in an unthinkably large amount of data? By using algorithms. These can be trained to separate signal (lepton decays) from background (anything else, really) better than humans. The problem here, however, is not only to find these lepton decays, but also find them in statistically significant numbers. If the Standard Model is correct, the τ → 3μ decays are so rare that their observations are below experimental sensitivity.
To come up with a more sensitive and scale-appropriate solution that would help physicists find evidence of the tau lepton decay into three muons at a statistically significant level, Yandex and CERN’s LHCb experiment have launched a contest for a perfect algorithm. The contest, called ‘Flavours of Physics’, starts on July 20th with the deadline for code submissions on October 12th. It is co-organised with an associated member of the LHCb collaboration, the Yandex School of Data Analysis, and Yandex Data Factory - a big data analytics division of Yandex - and is hosted on a website for predictive modeling and analytics competitions, Kaggle. The winning team or participant will claim a cash prize of $7,000, with $5,000 and $3,000 awarded to the first and the second runners-up. An additional prize in the form of an opportunity to participate in an LHCb workshop at the University of Zurich and $2,000 provided by Intel will be given to the creator of an algorithm that will prove to be the most useful to the LHCb experiment. The data used in this contest will consist both of simulated and real data, acquired in 2011 and 2012, that was used for the τ → 3μ decay analysis in the LHCb experiment.
Contest participants can build on the algorithm provided by the Yandex School of Data Analysis and Yandex Data Factory to make an algorithm of their own.
The metric for evaluation of the algorithms submitted for this contest is very similar to the one used by physicists to evaluate significance of their results, but is much more simple and robust thanks to the collective effort of the Yandex School of Data Analysis and LHCb specialists who have adapted procedures routinely used in the LHCb experiment specifically for this contest. Our expectation is that this metric will help scientists choose the algorithms that they could use on data that will be collected in the LHCb experiment in 2015, and in a wide range of other experiments.
Finding the tau lepton decay might take us out of the comfort zone of the Standard Model, but it just as well may open the door to extra dimensions, shed light on dark matter, and finally explain how gravity works on a quantum level.
Collisions as seen within the LHCb experiment's detector (Image: LHCb/CERN)
Forgetting the right to search
15 June, 2015
The State Duma Committee on Information Policy and Communications has discussed a bill that requires search engine operators to delete hyperlinks to illegal or unreliable information, or even reliable information that refers to events that happened three years ago or more, from their search results on requests from individuals and without a court order.
Internet search is our core business. In more than 15 years in this market, we have put colossal human and financial investments into our search engine, first and foremost, to offer our users search results that are complete, unbiased and useful. If this bill is passed in its current form, a search engine based on these principles will be difficult or even impossible to develop. That is why we feel it is important for us to offer commentary on this bill.
According to its authors, this bill enables any individual to control distribution of unreliable or outdated personal information on the internet. In principle, this gives people a right, which is based on one of the most basic human rights – the right to privacy, including the right to control access to information about oneself. Unfortunately, the procedure offered in this bill does not stop information from being distributed online, but contradicts the basic principles of law and current legislation.
The current law does not permit limiting a person's right to access reliable information. The Constitution of the Russian Federation guarantees everyone the right to freely seek, obtain, transfer, produce and disseminate information by any lawful means (Article 29). The Federal Act ‘On Information, Information Technologies, and Information Protection’ also stipulates an individual’s or organization’s right to search and obtain any information in any form from any source (Article 8). This is exactly what a search engine does – searches for information available through any public source. This bill ignores the right to search for information.
The limitations introduced by this bill reflect imbalance between private and public interests. The need to seek and obtain information often falls within public interest and concerns public figures, whose actions can have an impact on the general public or private lives. This bill impedes people's access to important and reliable information, or makes it impossible to obtain such information. If this bill is passed, the information about a clinic or a doctor, a school or a teacher one is considering to choose, may be impossible to find.
In addition, the procedure for requesting a search engine to remove hyperlinks introduced in this bill opens the door to numerous opportunities for misuse, as it doesn't require any evidence or justification. A search engine, on the other hand, is required to delete an undefined number or hyperlinks to indeterminate web pages. This loophole can very conveniently be used by unscrupulous businesses to undermine their rivals, or by criminals to facilitate fraud.
But even if we assume that it is possible to equal adequate information with inadequate or illegal information in the right to be searched for, one question remains: who will study the information which is searched for, and decide whether it is legal, adequate, relevant or reliable? The bill assigns this role to search engines, while the functions of the court or law enforcement agencies are given to individual commercial organizations. Failure to comply with this role is punished with penalties and litigations.
This bill also ignores the basic principles of information technology and information search. It gives any person the right to request a search engine operator to stop providing hyperlinks to web pages that contain specific information, but it does not require this person to say which hyperlinks should be removed. All they have to do is provide the information, hyperlinks to which they want to be removed. Instead of deleting hyperlinks to specific web pages from search results, a search engine is expected to stop retrieving a piece of information on any search terms and regardless of its location on the internet. For this to become plausible, a search engine operator would have to find all pages containing this information that might appear in any place in search results triggered by any search term that a human mind can come up with. This step alone would take eternity. The next steps would require a search engine operator to make sure that these pages do contain the information hyperlinks to which were requested to be removed, and then confirm that this information is indeed inadequate or older than three years old. It is obvious that this is an impossible task.
Even though the list of flaws of this bill can go further, it doesn't make sense discussing them all at a point when the stipulated procedure itself contradicts the law and is technically impossible.
The current bill is much less well thought through than the Google Spain v ARPD, González (C-131/12) decision by the Court of Justice of the European Union, which has been widely criticized, and which the Russian bill has often been likened to.
The links to be removed from search results mandated by the ruling of the Court of Justice of the European Union are specific, lead to specific information and appear on a narrow class of search terms. Hyperlink erasure is also considered on a case-by-case basis to make sure it does not limit access to important information or alter the balance between private and public interests.
Tune in to Yandex.Radio
4 June, 2015
Today we’ve announced our newly hatched personal ‘jukebox’ media player Yandex.Radio. This service will be appreciated by anyone wishing to always hear ambient music matching their personal preferences, or serving as a backdrop to anything they do or how they feel at any time of their day or night. The user interface of Yandex.Radio is simple and intuitive – it just lets you play the music that you will enjoy.
Yandex.Radio shares a catalogue of more than 20 million tracks with Yandex.Music, Yandex’s recommendation-based music streaming service, which was first launched in 2010 and re-launched after a major overhaul in 2014. While Yandex.Music helps listeners discover new music based on their interests and preferences, Yandex.Radio offers them the music that matches their current mood or activity.
Out of 10 million people currently tuning in to Yandex.Music every month, one million do this on their mobile phones. This million of people just like to have some background music while they are working out in a gym, driving to work, or chatting at a party. Alternatively, people choose their background music to match how they feel at the moment – cheerful or vigorous, moody or relaxed. Yandex.Radio is a service for those who like to choose their music based on their current activity or state of mind. The new service taps into the catalogue of Yandex.Music to offer these users more than a hundred stations to choose from – not only depending on their mood or current activity, but also on a genre or time period of music.
Yandex.Radio is now available on desktop, as well as on iOS- and Android-based devices. The personal recommendation technology in use on the Yandex.Music service has also been implemented in Yandex.Radio to play music based not only on the listener’s settings, but also their personal preferences, streaming history, and previous likes or dislikes.
The new personal jukebox player is currently available free of charge only to users in Russia. The revenue from the service will come from audio advertising, which is a novel format for our business. Just like traditional radio broadcasting, Yandex.Radio will feature audio ads, which in the future will be complemented with a graphic image or text both in the app and on the desktop service. Advertisers on Yandex.Radio will be able to enjoy all the advertising and audience targeting possibilities available to them on Yandex.Direct, as well as banner advertising.
New Concept Yandex.Browser Boosts Privacy and Launches as Beta
21 May, 2015
The minimalist concept version of our Yandex.Browser launched at the end of last year to respond to the highly interactive nature of contemporary web browsing is now available as a beta version, which is designed to also address the rising demand for personal privacy.
To meet the expectations of those users who would like to have more control over their digital footprint, we’re now rolling out a much more private beta version of the experimental Yandex.Browser, available in 15 languages, including English, German, Portuguese, Spanish and French.
Unlike in most browsers, sending the information about users’ behaviour to the developer (i.e. Yandex) in the private version of Yandex.Browser is disabled by default. While sharing browsing history and web cache can in principle be disabled in other browsers, this opportunity isn’t normally offered as a default option. Sharing users’ information helps developers better understand their behaviour and offer them a better browsing experience. The problem is that the right to make a decision whether to share this information is effectively removed from the user – few can find a pathway to customised privacy settings in a browser.
In addition to data sharing disabled by default, Yandex.Browser provides the ‘Stealth Mode’ option, which blocks analytics cookies, sharing plugins etc. This mode is activated by clicking a button conveniently located right next to the browser’s ‘smartbox’, a combined search and address bar, at the top of the screen. The source code of the built-in blocking extension was developed by AdGuard and is available on Github for anyone to see.
Safe browsing, as well as search suggestions appearing in the browser’s smartbox, is the feature indispensible for contemporary browsing that relies on sharing user information, albeit in an anonymised form. The safe browsing technology allows us to warn the user about unsafe websites. Each fraudulent or potentially harmful website that we identify in the process of indexing more than 30 million webpages every day is logged in our proprietary cloud database. Every time a user is about to visit a website, the website’s address is automatically checked against this database to see if it might be there and whether a warning should be shown.
We have modified the safe browsing technology to use it in our privacy-conscious version of Yandex.Browser. Instead of sending the full address of a website the user is about to visit to Yandex in order to check this address against the database of potentially harmful websites, Yandex.Browser only uses a fraction of a ‘hash’ of this website, which is checked against a ‘hashed’ database of potentially harmful websites on the user’s own computer. The browser uploads a ‘shell’ of this database to the user’s computer at the first launch. This database is then ready to be ‘filled’ with fractions of ‘hashed’ website addresses the user intends to visit. To keep this database updated and the user safe, Yandex.Browser synchs the database on the user’s computer with Yandex’s cloud database every hour, using only fractions of each hash.
Search suggestions in the browser’s smartbox give instant answers to users’ search queries without redirecting them to search results pages. The users of Yandex.Browser can at the first launch choose a default search provider from a selection of three, which varies depending on the user’s location.
To generate search suggestions, predict search terms and offer instant results without redirecting the user to the search results page, the browser has to share the search terms with the search provider as the user enters them into the browser’s smartbox. This option is enabled by default in Yandex.Browser. Although this type of data sharing can be disabled in settings, its benefits massively outweigh privacy risks. Also, web users have an opportunity to add any search provider they trust to the browser and set it as the default.
One of the flagship features of the new Yandex.Browser is rich search suggestions, which instantly take the user directly to the website, or even specific page on a specific website, via a widget and bypassing the search results page. Similarly, simple, straightforward searches in the smartbox of the new Yandex.Browser will retrieve simple and straightforward results right in the browser.
Other automated features essential for the contemporary web surfing, such as sending crash reports, resolving web navigation errors, or the autofill function, involve sharing users’ information in one form or another. These features remain enabled by default. The user has full control over this aspect of their browsing experience and can disable any or all of these features.
The beta version of experimental Yandex.Browser retains its minimalist look to offer the user unhindered experience interacting with the website. Browser tabs can now be toggled within groups, while tab groups can be moved within windows. Website information, the smartbox and favourite websites are hidden when not in use and can be summoned by clicking on the website’s header in Yandex.Browser.
Just like the alpha version of experimental Yandex.Browser, the beta version is available for Windows and OS X and can be downloaded at browser.yandex.com.
Yandex.Market Helps International Retailers Reach Russian Consumers
30 March, 2015
Russian online consumers are avid cross-border shoppers, and this trend is growing. According to a survey conducted by a market research firm GFK, about half of web shoppers in Russia made at least one purchase from an online retailer in EU, China or US last year, up from 36% in 2013.
Source: GfK, August-September 2014
While the most popular shopping destinations are traditionally the online market giants - AlibabaExpress and eBay - the niche for smaller businesses accepting payments from Russia and delivering shipments to this country is quickly expanding. Yandex.Market, a leading comparison shopping service, is in a position to accommodate the needs of international retailers wishing to sell their products to Russian customers by utilising all the benefits of a technologically advanced platform with over 16,000 stores, 68 million product offers and 22.3 million unique visitors per month (December 2014, comScore Media Metrix).
Now, international web stores have an opportunity to showcase their offers on Yandex.Market to target those customers who look to buy products specifically outside of Russia. Product search on Yandex.Market is designed to deliver the most relevant results with the best combination of customer service criteria, including time of delivery or specific payment options. This automatically gives domestic retailers an edge over international companies who are often limited in their customer service opportunities in Russia. Cross-border shoppers, however, are prepared to put up with longer delivery times or inconvenient payment methods for the sake of unique product selection or better price. They can now filter product offers from international stores from the millions of items available on Yandex.Market to instantly see them on top of other search results – including price in roubles, delivery options and a link to full product information.
According to GfK, product categories most popular with Russian consumers are clothing, makeup products, perfume, accessories and products for children and babies. International product offers in these categories are currently available on Yandex.Market and soon will be expanding to add new groups, which continuously grow in popularity, such as consumer electronics and gadgets from Chinese retailers, for instance.
Any online store anywhere in the world can join Yandex.Market by providing customers with a landing page in Russian, an opportunity to have their purchase delivered to a Russian address, as well as an opportunity to pay for purchases in Russia via a bankcard or electronic money. International retailers will soon be able to benefit from a universal payment solution provided by Yandex, which will allow web stores outside of Russia to receive payments from Russian customers regardless of their method.
Dozens of retailers, including UK's Asos.com, China's LightInTheBox, Germany's Kidsroom.de, a US website Shopbop.com, and Italian Yoox, are already offering their products to Russian consumers via Yandex.Market, and with the new functionality their number is expected to grow.
Yandex Data Factory Predicts ‘Churn’ for World of Tanks
2 March, 2015
Customer loyalty and satisfaction is crucial in community-based gaming, where every single player matters, and devoted, experienced gamers are especially valuable for the game. Our big data unit,Yandex Data Factory, took game churn prediction – knowing how many gamers are likely to leave the game – to another level. Wargaming, an international MMOG developer, whose game World of Tanks, one of the world’s most financially successful games, with over 100 million registered players, can now determine more accurate which players are likely to stop playing soon and take measures to prevent that.
The challenge presented to the YDF team was to help increase WoT players’ loyalty and satisfaction with a minimal effort and at a minimal cost. To approach this challenge, a sample dataset of 100,000 random players who had 20 games or more in the past year was selected – this was done to exclude those who joined the game by accident or just to have a try. Based on a similar concept used in telecom and Wargaming’s own understanding, YDF analysts defined a ‘churner’ as a player who had zero games in the month following a gaming session. Next, the raw data for the ‘churners’, which included over 100 parameters – personal (obfuscated payment balances, purchase logs, etc.), as well as gaming (game logs, number of battles, battle types, number of destroyed tanks, clan battles data, free experience etc.) – was fed to our proprietary machine-learning algorithm, MatrixNet, to find similarities in gamers' behaviour and personal profiles. In result, a probability of churn was assigned to every gamer in the dataset.
WoT could then apply this churn prediction formula to the whole gaming community to spot top potential churners and target customer retention measures, such as special offers, new frictions, bonuses or community activities, specifically to them. The accuracy of YDF formula’s churn prediction measured at least 20-30% better than the current standard used in the gaming industry. Churn prevention – developing a formula for personalised retention measures – is the next challenge that YDF is ready to take on. Read more about YDF's churn prediction project for Wargaming.
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