• Crime, Race and Lethal Force in the USA — Part 3

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    This is the concluding part of my article devoted to a statistical analysis of police shootings and criminality among the white and the black population of the United States. In the first part, we talked about the research background, goals, assumptions, and source data; in the second part, we investigated the national use-of-force and crime data and tracked their connection with race.
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  • Crime, Race and Lethal Force in the USA — Part 1

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    Do the police in the US really shoot black people more often than white people? Is use of lethal force connected with race? How is crime related to race? What are the odds of getting shot by the police if you are white and if you are black? We're taking public data and python with pandas to shed some light on these questions, propaganda and politics set far aside.
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  • 10 Best Email Scraping Tools for Sales Prospecting in 2020

    We all know how hard it is to build an email sales list from scratch, especially for small companies. There left no options due to limited resources. In fact, many companies even buy preset profiled lists from the third party and send identical mass emails. It can put your business in a vulnerable position ascribed into the low quality of the email lists. However, there is a better way to build a highly targeted email list with email scraping tools.

    Email scraping can help you collect email addresses shown publicly using a bot. What makes this great is that you have control over where to get the email lists from, and who can opt-in. Moreover, you don’t have to rely on the second-hand source. I profiled a list of best 10 email scraping tools for sales prospecting. Let’s take a look.

    1. Zoominfo

    A full-featured email scraping platform with a comprehensive database. You can directly search for titles and companies within their platform. It is more like a directory system that covers professionals in all industries with contact information. Email lists are the assets. That said, it comes with a price tag. It is worth to invest if you are looking for accurate sales leads. Zoominfo is an excellent option for enterprise-level sales prospects.

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  • How to find an English teacher. Part 1


      In the modern world, here and there ideas are arising about using data science for an extra benefit. For instance, Google can use a history of watched videos for providing recommendations about new ones. Online shops are using a recommendation system for increasing your receipt. However… if companies use the data for their benefit, could we do the same for own needs such as looking an online English teacher?


      Disclaimer

      It is an approach based on my own experience and can be unsuitable to your point of view, ideas, or principles.

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    • Approach to calculating individual risk in COVID-19

        In February 2020, when the disease came to Europe, it became apparent to me that our timid hopes that the epidemics would subside and be finally buried in the China's soil were ruined. It was already evident from the Chinese statistics that the virus is lethal enough to scare and mild enough to pass unnoticed in many cases and, thus, to guarantee its effective dissemination. The question was when it reaches each next country.




        Another question was the individual risks, especially the risk of lethal outcome if one contracts the virus. The average figure of around 5% was circulated by late January and early February. It was known that males were more susceptible to fatal outcomes. By February, it was also evident that the virus doesn't lead to death only in the elderly — the middle age was significantly affected, as well.

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      • When the COVID-19 pandemic will end

          Dear all,


          I am the head of Data Science at British Transport Police, and one of our department tasks is to efficiently allocate staff, depending on the crime rates, which correlate to passenger flow. As you understand, the passenger flow will undertake significant change as soon as the Government decides to cancel quarantine or stop some limitations. The question naturally arises: when will the pandemic end and how to prepare for a return to normal life.

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        • AdBlock has stolen the banner, but banners are not teeth — they will be back

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        • COVID YAAA! or Yet Another Analyze Attempt

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            Hello, Habr!


            About a month ago, I had a feeling of constant anxiety. I began to eat poorly, sleep even worse, and constantly read to a ton of news about the pandemic. Based on them, the coronavirus either captured, or liberated our planet, was either a conspiracy of world governments, or the vengeance of the pangolin, the virus either threatened everyone at once, or personally me and my sleeping cat…


            Hundreds of articles, social media posts, youtube-telegram-instagram-tik-tok (yes, I sin) content of varying degrees of content quality did not lead me to anything but an even greater sense of anxiety.


            But one day I bought buckwheat decided to end it all. As soon as possible!

            What did you do?
          • «Build it & Break it»: How some algorithms generate captcha, while others crack it

            Hello, Habr! Let's me present you a translation of an article "«Ломай меня полностью!» Как одни алгоритмы генерируют капчу, а другие её взламывают", author miroslavmirm.

            Doesn't matter what kind of intelligence you have — be it artificial or natural — after this detailed analysis no captcha will be an obstacle. At the end of the article, you can find the simplest and most effective workaround solution.

            CAPTCHA is a completely automated public Turing test to tell computers and humans apart by automatically setting up specific tasks that are difficult for computers but simple for human. This technology has become the security standard used to prevent automatic voting, registration, spam, brute-force attacks on websites, etc.
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          • Using Data Science for house hunting in Montreal

              Introduction


              I happen to live in Montreal, in my condo on the edge of McGill Ghetto. Close to Saint Laurent Boulevard or the Maine as locals call it, with all it's attractions — bars, restaurants, night clubs, drunken students. And once upon a time, on a particular lively night, listening to the sounds of McGill frosh students drunkenly heading home after hard night of studying. I thought, that it might be a good idea to move into my own house, a little bit further away from the action.


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            • Free API Moscow Stock Exchange (MOEX) in Google Sheets

                Last year the number of private investors at Moscow Stock Exchange (MOEX) has doubled and reached 3.86 million: about 1.9 million people have opened accounts at MOEX in 2019. The Saint Petersburg Stock Exchange which specializes in trading of foreign company shares has seen its accounts increase three times from 910,000 to 3,06 million over the past year.



                This means that almost 2 million newbies without any actual trading experience and lacking any specialized software for trading/position analysis have entered the market.
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              • Machine Learning for your flat hunt. Part 2

                  
                  Have you thought about the influence of the nearest metro to the price of your flat? 
                  What about several kindergartens around your apartment? Are you ready to plunge in the world of geo-spatial data?


                  The world provides so much information…
                  
                  

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                • Contextual Emotion Detection in Textual Conversations Using Neural Networks


                    Nowadays, talking to conversational agents is becoming a daily routine, and it is crucial for dialogue systems to generate responses as human-like as possible. As one of the main aspects, primary attention should be given to providing emotionally aware responses to users. In this article, we are going to describe the recurrent neural network architecture for emotion detection in textual conversations, that participated in SemEval-2019 Task 3 “EmoContext”, that is, an annual workshop on semantic evaluation. The task objective is to classify emotion (i.e. happy, sad, angry, and others) in a 3-turn conversational data set.
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                  • How do you choose products in stores?

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                    The most important single ingredient in the formula of success is knowing how to get along with people. Theodore Roosevelt

                    In the previous article I tried to cover the basics of pricing analytics. Now I'd like to talk about something more interesting.

                    Have you ever thought about why you choose certain products in stores, why you prefer them to other similar ones? Many shopping trips are spontaneous, so it's probably impossible to give a clear answer for all the times you go shopping. But the general idea is obvious: you go shopping for a specific reason (to get food, a gadget, for entertainment, to play blackjack). In this article I'm going to use available data from grocery retailers to talk about how a set of basic logical assumptions and community analysis can help us determine the way customers choose products.
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                  • A selection of Datasets for Machine learning

                      Hi guys,

                      Before you is an article guide to open data sets for machine learning. In it, I, for a start, will collect a selection of interesting and fresh (relatively) datasets. And as a bonus, at the end of the article, I will attach useful links on independent search of datasets.

                      Less words, more data.

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                      A selection of datasets for machine learning:


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                    • .NET, TensorFlow, and the windmills of Kaggle — the journey begins

                      This is a series of articles about my ongoing journey into the dark forest of Kaggle competitions as a .NET developer.

                      I will be focusing on (almost) pure neural networks in this and the following articles. It means, that most of the boring parts of the dataset preparation, like filling out missing values, feature selection, outliers analysis, etc. will be intentionally skipped.

                      The tech stack will be C# + TensorFlow tf.keras API. As of today it will also require Windows. Larger models in the future articles may need a suitable GPU for their training time to remain sane.
                      Let's predict real estate prices!