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Category: Data Science

  • Business Intelligence Trends 2019: AI for Data Management

    Bi and Data Management

    Today, the digitization of businesses is in high gear. Digitally mature businesses harness exceptional opportunities. They can attract a larger audience, better predict consumer needs, automate in-house operations, save time and expenses. Business Intelligence (BI) is a tech-driven process for analyzing data. It implies that emerging technologies are extremely important for the BI industry. Latest…

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  • AI in Logistics: Data-Driven Shifts to Boost Your Business

    AI in logistics and transportation

    AI technologies in 2019 are not a luxury but a necessity for organizations to achieve and maintain their competitive edge in the field of logistics. According to Forbes Insight research, 65% of the industry leaders believe that logistics, transportation, and supply chain have ushered in the era of “profound transformation.” The report by Accenture reveals…

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  • 4 Ways to Leverage Data Science for Business Endeavors

    data science for business endeavors

    Businesses across different industries face, however, similar obstacles on the road to success. Among such constraints are time-consuming manual tasks, poor conversion rate, low productivity, etc. As Gartner says, “Data scientists hold the key to unveiling better solutions to old problems.” There are lots of data science techniques that can be successfully used to build…

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  • 5 Predictions for Artificial Intelligence in 2019: Analytics, Industries, Approaches, Ethics, Job Creation

    AI Predictions

    Humanity has long been obsessed with the potential of computerization and robots. The concept of artificial mind hasn’t appeared out of anywhere. Previously, artificial intelligence (AI) was vigorously discussed in the domain of science fiction. But those days can rightly be seen as the cradle of AI and approaches of employing it in the way…

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  • The Most Exciting Uses of Image Recognition That are Already Changing Our Lives

    uses of image recognition

    Image recognition has been a topic on our blog a few time before. It’s a technology that has not stopped gaining popularity for some time now, and we wanted to take a look at what other interesting and even non-conventional ways image recognition makes a difference in different industries today. Image Recognition in Healthcare Do…

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  • Human-in-the-Loop Computing Paradigm: Machine Learning with Human Input

    Are we heading towards the future of machines that learn and perform all by themselves? With the recent advancements in deep learning, it may seem so, but some experts disagree. Human-in-the-Loop approach to machine learning is gaining popularity as the best approach to training more accurate models. What value can it bring to a machine…

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  • Feature Engineering as a Core of Machine Learning Business Value

    Feature Engineering as a Core of Machine Learning Business Value

    “How can we ensure the success of our machine learning project?” Your business has asked this questions. Your competitors have asked this question. Unfortunately, there is no straightforward answer, but a good candidate could be feature engineering. Some data scientist described it as a bottleneck, other as a superpower. Either way, all of them agree…

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  • Latest Trends on Computer Vision Market

    Trends on Computer Vision Software Market

    Computer vision is changing industries and making the lives of consumers not only easier but also more interesting. As a field, computer vision has received a lot of publicity and a decent amount of investment. The North American computer vision market has had a total investment of $120 million USD, while the Chinese market surged…

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  • How Face Recognition Technology Shapes the Future across Multiple Industries

    face recognition technology

    The last decade has been a good one for face recognition technology. Although it has existed since the 1960s, any large-scale attempts to successfully implement it failed. The main reason being that it lacks precision and scalability. Everything changed in the late 2000s. In 2011, both the Pinellas County Sheriff’s Office and Panama’s Tocumen airport…

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  • How to Use Semantic Search to Increase Conversion

    semantic search

    The concept of the semantic search was first introduced in already in 1998, but it remained mostly a theoretical concept until 2012 when Google, Facebook and Bing started launching their own products using semantic search. Two trends pushed semantic search from concept to reality: an increase in long tail searches and a demand from users…

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