The previous version of AlphaGo beat the human world champion in 2016. The new AlphaGo Zero beat the previous version by 100 games to 0, and learned Go completely on its own. We examine what this means for AI.
There is a big demand of quick insights or real time analytics from business side. But traditional BI or data warehouse architectures lack this realtime functionality. Here we discuss realtime analytics architecture in details.
The rise of high information advances, for example, Big Data, Machine Learning (ML), and the Internet of Things (IoT) in the Data Management scene has now started another enthusiasm for Data Governance.
We rank 23 open-source deep learning libraries that are useful for Data Science. The ranking is based on equally weighing its three components: Github and Stack Overflow activity, as well as Google search results.
AI technology involves a change in the value chain and represents a major challenge and opportunity for businesses. Managers are directly involved in this challenge, by accompanying the teams through this transition: vanquish fears, embracing innovation, transforming businesses, training teams.
I learned how important to understand data before running algorithms, how important it is to know the context and the industry before jumping on getting insights, how it is very easy to make models but tough to get them to work for you, and finally, how it only takes one line of code to run linear regression on your dataset.
The most anticipated aspect of the RE•WORK Deep Learning Summit Montreal was the assembly of deep learning pioneers Yoshua Bengio, Yann LeCun, and Geoff Hinton on stage separately and together for the first time at such an event.
At the Deep Learning Summit in Montreal last week, we saw Yoshua Bengio, Yann LeCun and Geoffrey Hinton come together to share their most cutting edge research progressions as well as discussing the landscape of AI and the deep learning ecosystem in Canada.
After completing the 3 most popular MOOCS in deep learning from Fast.ai, deeplearning.ai/Coursera (which is not completely released) and Udacity, I believe a post about what you can expect from these 3 courses will be useful for future Deep learning enthusiasts.
Strata is a conference I very much enjoyed attending. This year, I observed a few common themes that ran across much of the conference content: Data Science Collaboration, Data Ethics, and Platform Optimization.
This blog explores how the massive parallel processing power of the GPU is able to unify the entire AI pipeline on a single platform, and how this is both necessary and sufficient for overcoming the challenges to operationalizing AI.