Last week Phys.org burst in news: the startup of LightOn offered alternative to central processors (CPU) and graphic processors (GPU) of a solution of tasks of the analysis of big data. The group of authors is based in Pierre and Marie Curie University, Sorbonne and all other correct places in France. The solution is based on optical analog data handling "with light speed". Sounds interestingly. As in the press release there were no scientific and technical details, it was necessary to look for information in patent databases and on the websites of universities. Results of investigation under a cat.
Coursera and other MOOS'I – very entertaining and tightening piece. Thanks to them it is possible to learn much, to learn a lot of things. It is important to have only access to a network and not to be lazy. In all Moos'ovskoy of history the same rule works, as when writing the master's thesis: "If it is not ready to do every day on slightly, better be not accepted at all". Following it, it is possible to cope both with a data science, and with introduction to artificial intelligence, and even with quantum physics …
1 year, 9 months ago
As to the first-year student of University Innopolis often ask me a question, than we are engaged here. Especially for a habr I wrote the narration how we "sawed" the project on DMD.
Attention! The author does not guarantee that his jokes will be clear and ridiculous.
1 year, 9 months ago
If you know why after execution of 'hset mySey foo bar' we will spend not less than 296 bytes of random access memory why engineers of instagramm do not use line keys why it is always worth changing hash-max-ziplist-entries/hash-max-ziplist-val and why the data type which is the cornerstone of hash it and part of list, sorted set, set — do not read. For the others I will try to tell about it. The understanding of the device and work a hash of tables in Redis is crucial when writing systems where the economy of memory is important.
About what this article — what expenses incurs Redis on storages of the key that such ziplist and dict when and for what they are used how many borrow in memory. When hash is stored in ziplist when in dicth and that it gives us. What councils from fashionable articles about optimization of Redis you should not perceive seriously and why.
We continue a series of analytical researches of a demand of skills in labor market. This time thanks to Pavel Surmenk of sharky we will consider a new profession – Data Scientist.
The last years the term Data Science began to gain popularity. Write about it much, speak at conferences. Some companies even employ people to a position with the sonorous name Data Scientist. What is Data Science? And who such Data Scientists?
If to go straight all yes directly, far you will not leave … (Little prince, Antoine de Saint-Exupéry)
Recently the colleague somehow appealed to me to help with Teradata. It is actively implemented now and the first step of this implementation is data loading on a daily basis. It is necessary to fill in much and as soon as possible. Some alternative methods of data loading asked to find me in Teradata which not strongly would depend on the resources selected to the user. In the course of this work I had to become more closely acquainted with .NET Data Provider for Teradata. An input of acquaintance some curious parts which knowledge, in my opinion, can be very useful became clear. As not all know about Teradata, I will begin with its short description.
Pleasant news to all who have no opportunity to be trained in Technopark, the Technosphere or Tekhnotreke: now courses of these projects are available in the form of online courses on the Stepic platform! Today record on five disciplines is available:
Over time the quantity of courses will be increased.
Why we do it? Quite obviously: not everyone can become the listener of our projects, only pupils from three Moscow higher education institutions can take part. And thanks to online training also many other talented students will be able to gain knowledge, so useful to the beginning IT specialists. Within online courses pupils will be able to watch content interesting by it and to perform practical tasks for check of the acquired material. Besides, they will have an opportunity to communicate with each other, to discuss tasks and to ask questions online. Following the results of successful passing of a course the certificate will be issued. And now is more detailed about available disciplines.
In general, circles can tell a lot of things about school. A large number of sports sections, probably, speaks about existence of good halls and the equipment. The prices of circles, perhaps, speak about a kommertsializirovannost of school in general. Besides it was interesting to look whether the number of paid services influences success of school. Whether help to try to obtain a mug of the best rezult at examinations and the Olympic Games.
On pgu.mos.ru there is a section where it is possible to write the child in section. In night all this section was extorted and we on hands had information about 80 000 Moscow circles.
1 year, 9 months ago
Purchases of each client in shop only at first sight seem unique. At buyers identical behavior models on the basis of requirements, for example, purchase of milk and bread every other day, packs of cigarettes every evening, chocolates to tea, yogurt and croissant by a lunch, etc. are developed. And as, anyway, needs of people match, we can speak about typical consumer behavior in certain conditions.
The analysis of consumer baskets assumes studying of communications and patterns in behavior of clients of a distribution network. Results of the analysis help to create target marketing activity, to create the personalized sentences and to plan promo for increase in the average check and profit.
We already described the analysis of consumer baskets here, and in this article, we will consider comparison of typical baskets and the possibility of use of results in business processes of a retail. The possibility of visualization and comparison of baskets with similar goods helps the retailer to select quickly patterns in consumer behavior and to make the necessary decisions for optimization of the activity.
1 year, 9 months ago
Today we announce new technology Meteum — now with its help to Yandex. Weather will build own weather forecast, but not to rely only on data of partners as it was earlier.
And the forecast will be separately calculated for each point from which you request it and to be recalculated every time when you look at it to be the most actual.
In this post I want to tell a little about how presently the world of weather models is arranged, than our approach differs from normal why we decided to build own forecast and why we believe what at us will turn out better, than at all others.
We constructed own forecast with use of traditional model of the atmosphere and the most detailed grid, but also tried to collect all possible sources of data on atmospheric conditions, statistics on how weather in practice behaves, and applied machine learning to these data to reduce error probability.
Now in the world there are several main models on which forecast the weather. For example, model open source WRF, the GFS model which initially were the American development. Now the NOAA agency is engaged in its development.