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Here you’ll find all the latest thinking in Data Science along with case studies, company news and other useful resources to move your business forward in Big Data Analytics.
  • 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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  • How OCR Can Help Employees Fight Through Most Mundane Tasks

    optical character recognition

    These days, office employees need an AI hero. Can you imagine the number of hours wasted on handling a paper-based workflow? Isn’t it time to save employees from piles of paper? No one is saying it will be easy to eliminate paper documents promptly. For instance, in the legal sphere where the cost of a…

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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 Software Market

    Trends on Computer Vision Software Market

    Computer vision software 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 market for computer vision software has had a total investment of $120 million USD, while the…

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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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  • What is Predictive Models Performance Evaluation and Why it is Important

    Predictive Models Performance Evaluation

    Predictive models have become a trusted advisor to many businesses, and for a good reason. These models can “predict the future”, and there are many different techniques available, meaning any industry can find one that fits their particular challenges. However, the abundance of predictive modeling techniques and software libraries means that there are multiple models…

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  • Deep Learning: Strengths and Challenges

    deep learning strengths and challenges

    Deep learning is largely responsible for today’s growth in the use of AI. The technology has given computers extraordinary powers, such as the ability to recognize speech almost as good as a human being, a skill too tricky to code by hand. Deep learning has also transformed computer vision and dramatically improved machine translation. It…

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