Optimizers are needed to find the optimal solution for the given task. Optimizers associate themselves with cost function and model parameters together by updating the model. i.e. when you want to identify weights that minimize your mean squared error in linear regression, you need to use some function to find parameters such that mean squared …
Deep learning is pattern recognition via so-called neural networks. Neural networks are a set of algorithms, modeled after the human brain. They are sensors: a form of machine perception. Deep learning is a name for a certain type of stacked neural network composed of several node layers. Each layer’s output is simultaneously the subsequent layer’s …
Using GPU for deep learning has seen a tremendous performance. It has been reported that execution time using GPU is 10x -50x times faster than CPU-based deep learning and It is also a lot cheaper than CPU-based system. You can see this below in the picture. I was curious to check deep learning performance on …
Neural networks have been the most promising field of research for quite some time. Recently they have picked up more pace. In earlier days of neural networks, it could only implement single hidden layers and still we have seen better results. Deep learning methods are becoming exponentially more important due to their demonstrated success …
Machine learning is a very successful technology but applying it today often requires spending substantial effort hand-designing features. This is true for applications in vision, audio, and text Any machine learning algorithm performs as good as provided features are. Let’s understand this by using image classification example. When we try to classify an image into …
Feature Learning , Deep Learning and Machine learning Read More »