Dataconomy

NOVEMBER 7, 2018

With the help of a use case, Dr Patrick Vetter, Head of Competence Center Data Science at Supper and Supper GMBH explains how a deep learning methodology can locate and segment wind turbines on satellite imagery. As a pioneer in fighting global climate change, Germany is increasingly investing in renewable. The post How Deep Learning can solve the problem of global climate change appeared first on Dataconomy.

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Depends on the Definition

NOVEMBER 23, 2018

This is the first post of my series about understanding text datasets. A lot of the current NLP progress is made in predictive performance. But in practice, you often want and need to know, what is going on in your dataset.

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Explosion

NOVEMBER 21, 2018

Who’s going to "win at AI"? There are now several large companies eager to claim that title. Others say that China will take over, leaving Europe and the US far behind. But short of true Artificial General Intelligence, there’s no reason to believe that machine learning or data science will have a single winner. Instead, AI will follow the same trajectory as other technologies for building software: lots of developers, a rich ecosystem, many failed projects and a few shining success stories.

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Dataconomy

NOVEMBER 16, 2018

Perhaps even moreso than even big data or blockchain, AI is fast becoming the buzzword on everyone’s lips. Machine learning has been a promising field for years, but with the astonishing success of deep learning techniques, we’re rapidly being propelled into an automated future. But can AI withstand the hype? The post Is AI Just a Buzzword? 4 Experts Weigh In on the Future of AI appeared first on Dataconomy.

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Dataconomy

NOVEMBER 8, 2018

Organizations yearn order and simplicity over chaos and confusion, but the data-driven era we live in challenges these desires on a daily basis. Seemingly every day, massive amounts of transactional and streaming data is being introduced into enterprises. This data must be collected, deciphered, shared, and acted upon. Cloud-native technologies. The post Kubernetes Meets Big Data appeared first on Dataconomy.

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Dataconomy

NOVEMBER 21, 2018

Last year, we set up a prediction model on crime in London. We had established the model already, grounded in open data, but updated it to make predictions about 2017. We took the data provided by the police in the greater London area, and by enriching this data with Points. The post How Effective Is AI Crime Prediction? Evaluating Our London Crime Prediction Model appeared first on Dataconomy.

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Dataconomy

NOVEMBER 16, 2018

In terms of pioneering data-based technology, IBM are the gold standard. Indeed, IBM has held the record for receiving the most patents every year for the past 25 years and has developed countless revolutionary technologies, from SQL to the world’s fastest supercomputer. It should come as no surprise that IBM. The post IBM Watson IoT’s Chief Data Scientist Advocates For Ethical Deep Learning and Building The AI Humans Really Need appeared first on Dataconomy.

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Dataconomy

NOVEMBER 8, 2018

An insider tip: if you’re looking for the real inside track on tech innovation at a conference, look to the startups. Undoubtedly the larger companies have the resources and brainpower to fuel the innovations of tomorrow, but many of the nascent ideas which will revolutionise the ways we live and. The post 5 Startups & Scaleups To Watch Out For at DN18 appeared first on Dataconomy.

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Dataconomy

NOVEMBER 15, 2018

It’s no news that unstructured data has been a highly sought after source since its inception, first for determining public topical insights and now for training machine learning algorithms. The critical question to answer is whether you should outsource the collection to overcome business challenges or not? Mike Madarasz explains. The post Why Outsourcing Social Media Data Access is a Good Thing appeared first on Dataconomy.

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Dataconomy

NOVEMBER 15, 2018

It’s no news that unstructured data has been a highly sought after source since its inception, first for determining public topical insights and now for training machine learning algorithms. The critical question to answer is whether you should outsource the collection to overcome business challenges or not? Mike Madarasz explains. The post Why Outsourcing Social Media Data Access is a Good Thing appeared first on Dataconomy.

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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