As 2020 comes to an end, Deep learning turns out to be the most coveted jargon of this decade. Though the core foundations of deep learning have been led many years ago, with papers related to neural networks and LSTM architectures being published since late 80s, dots didn’t seem to connect practically till the early years of this decade. This revolution really began with 2012, AlexNet paper that proposed a multi-layer neural network architecture with operations like convolutions and max-polling to classify images in the ImageNet Dataset. Before we talk about AlexNet let’s briefly discuss the ImageNet Dataset. This dataset…

Bhavin Jawade

Researcher and Graduate student at University at Buffalo. Software Engineer at Persistent Systems.

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