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 […]
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 […]
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 […]