As showed in the last post, machine learning is great for pattern recognition. But it’s getting so much powerful that can be used in much more areas than only pattern recognition, such as: Drug Discovery and toxicology Discovering new treatments for human diseases is one of the most complicated tasks […]
Deep Learning Application Areas – Science and Corporate Read More
Since it’s revival in 2006, Deep learning advanced so quick that is used in many aspects of modern society such as: Deep Learning Analytics Companies such Google and Microsoft have access to large volumes of data, social media organisations such as Facebook, YouTube and Twitter have billions of users that
Deep Learning Application Areas – Pattern Recognition Read More
[vc_row fullwidth=”false” attached=”false” padding=”0″ el_class=”whatsnew”][vc_column width=”1/2″][vc_column_text disable_pattern=”true” align=”left” margin_bottom=”0″]*Integration & API’s powered by António Queiroz* <*BLOG* It’s becoming more and more important for companies to invest in an Integration Platform that can support their most critical asset: Data. Read more… <*BLOG* I did more than attending TIBCO Now ’17 User conference
There are several ways to process and integrate data but due the lack of standards and the heterogeneity of the “things”, a key role is played by the middleware. Middleware is application-independent software that provides services that allow communications between applications. Middleware hides the complexities of the lower layers, like operating
As seen in the last post, after the event of CNN’s (Convolutional Neural Networks) we step in the second AI Winter, but in 2006 this would change… 2006: Deep Learning Arises In 2006, Hinton, Simon Osindero and Yee-Whye Teh published a paper where they solved the vanishing or exploding gradient problem. In
A Deep Learning history walk through – Deep Learning Arises Read More
Deep Learning is one the last iterations on the evolution of Machine Learning. One evolution that started with something as simple as Linear Regression, and despite all the difficulties and winters that grassed for, it has been an area whose advances have generated a tsunami that has waves that reached
A Deep Learning’s history walk through Read More
What should you take into account when selecting an integration platform? Technology adviser Matthias Meijer presented 4 aspects of the latest Tibco product you might want to consider. “Easy Process, Service and API Implementation” To solve integration problems you need: A “fast and agile” workspace development environment, facilitating (usually
Choosing an integration platform: factors to consider Read More
Edge computing takes localised processing a bit further than Fog Computing, because it allows for actions to be taken on-site, in the processing point. This poses an advantage over Fog Computing as there are less points of failure. Each item in the chain is more independent and capable of determining
Even though Cloud computing is a great way of processing the data generated by the “things”, it doesn’t meet all IoT’s needs. For instance, one issue that affects the quality of service (QoS) severely is network latency. Real time applications are affected by the delay caused by latency in networks
[vc_row fullwidth=”false” attached=”false” padding=”0″][vc_column width=”1/1″][vc_column_text disable_pattern=”true” align=”left” margin_bottom=”0″]May suggestions from our Polarising Evangelists about the world of technology. Two more new articles of IoT and another one of Integration, among other relevant news. Thank you for joining us! [/vc_column_text][/vc_column][/vc_row][vc_row fullwidth=”false” attached=”false” padding=”0″ el_class=”whatsnew”][vc_column width=”1/2″][vc_column_text disable_pattern=”true” align=”left” margin_bottom=”0″]*Integration & API’s powered