Do you need artificial intelligence and machine learning expertise in house?

Developing artificial intelligence expertise is a challenge. There’s a huge global demand for practitioners with the right skills and knowledge and a lack of people who can actually deliver what’s needed. It’s difficult because many of the most talented engineers are being hired by the planet’s leading tech companies on salaries that simply aren’t realistic for many […]
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How can Artificial Intelligence support your Big Data architecture?

Getting a big data project in place is a tough challenge. But making it deliver results is even harder. That’s where artificial intelligence comes in. By integrating artificial intelligence into your big data architecture, you’ll be able to better manage, and analyze data in a way that provide a substantial impact on your organization. With big data getting even […]
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Quantum computing, edge analytics, and meta learning: key trends in data science and big data in 2019

When historians study contemporary notions of data in the early 21st century, 2018 might well be a landmark year. In many ways this was the year when Big and Important Issues – from the personal to the political – began to surface. The techlash, a term which has defined the year, arguably emerged from conversations and […]
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5 best practices to perform data wrangling with Python

Data wrangling is the process of cleaning and structuring complex data sets for easy analysis and making speedy decisions in less time. Due to the internet explosion and the huge trove of IoT devices there is a massive availability of data, at present. However, this data is most often in its raw form and includes a lot […]
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What is the Carbon Footprint of AI and Deep Learning?

Most of the recent breakthroughs in Artificial Intelligence are driven by data and computation. What is essentially missing is the energy cost. Most large AI networks require huge number of training data to ensure accuracy. However, these accuracy improvements depend on the availability of exceptionally large computational resources. The larger the computation resource, the more energy it consumes. This […]
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