Brew Some Deep Learning Using Caffe

Shanosh Kumar is technology journalist at EFY. He is BCA from Bangalore University and MBA from Christ University, Bengaluru


In reality, we are building features into machines using such specialised software and letting these connect to smart, artificial neural networks and frameworks to learn for themselves.

Significantly, these machines not only learn the features but run based on real-world events, where Caffe could work on cameras for combining, classifying and, to an extent, making intelligent decisions like informing concerned authorities through email or message alerts in places like a bank ATM, in case of unrecognised movement or threat.

With improvements in processing power and graphics, the bottlenecks of computation are being overcome over the years. Deep learning has already branched out to many other use cases. Text analytics, time-series analytics, image processing and real-time threat detection using video or motion detection are areas that are using deep learning techniques.

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