Want a fun way to quickly convert photos and images into the style of masterpiece paintings and drawings?
It’s almost impossible to escape the impact frontier technologies are having on everyday life.
At the core of this impact are the advancements of artificial intelligence, machine learning, and deep learning.
This week is all about AI: Intel’s new AI processor, OpenAI and Microsoft team up, Google brings GPUs to the cloud and invests in a Montreal AI research group.
Last week we introduced the named entity recognition algorithm for extracting and categorizing unstructured text.
In this post we’ll show you how to get data from Twitter, clean it with some regex, and then run it through named entity recognition. With the output we get from the algorithm, we can then group the data by the category each named entity is assigned to, and then extract the categories we are interested in.
If you’re headed to AWS re:Invent 2016 in Las Vegas this year, be sure to catch our panel Bringing Deep Learning to the Cloud with Amazon EC2 (CMP314) on Thursday, December 1st at 2:30pm in the Sands Showroom at the Venetian.
Deep learning is a machine learning technique used to solve complex problems related to image recognition, natural language processing, and more.
It’s fun way to convert photos or images into the style of a masterpiece painting, drawing, etc. For instance, you could apply the artistic style of Van Gogh’s Starry Night to an otherwise boring photo of the Grand Canal in Venice, Italy.
This week we take a deep dive into augmented reality and try on Snapchat Spectacles, we learn how easy it is to steal your face with some cardboard glasses, and why Apple’s working on their own Google Glass project.
Plus, we check out Facebook’s new photo filters, and what AI can and cannot do right now. Read More…
Unstructured text content is rich with information, but it’s not always easy to find what’s relevant to you.
With the enormous amount of data that comes from social media, email, blogs, news and academic articles, it becomes increasingly hard to extract, categorize, and learn from that information.