One of the most useful and emerging applications in the ML domain nowadays is using the transfer learning technique; it provides high portability between different frameworks and platforms. Once you’ve trained a neural network, what you get is a set of trained hyperparameters’ values. For example, LeNet-5 has 60k parameter values, AlexNet has 60 million, and VGG- 16 has about 138 million […]
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A deep-belief network can be defined as a stack of restricted Boltzmann machines in which each RBM layer communicates with both the previous and subsequent layers. The nodes of any single layer don’t communicate with each other laterally. This stack of RBMs might end with a Softmax layer to create a classifier, or it may […]
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Training a network using a distributed system This is useful when your network is large enough that the matrix multiplications involved in training become unwieldy on a traditional PC. This problem is particularly prevalent when you have harsh time constraints (e.g. online training). If your thinking about a distributed system because you want to fiddle […]
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Simulated annealing was developed in the mid 1970s by Scott Kirkpatrick and several other researchers. It was originally developed to better optimize the design of integrated circuit (IC) chips by simulating the actual process of annealing. Annealing is the metallurgical process of heating up a solid and then cooling it slowly until it crystallizes. The […]
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Genetic Algorithms Both genetic algorithms and simulated annealing are evolutionary processes that may be utilized to solve search space and optimization problems. However, genetic algorithms differ substantially from simulated annealing. Simulated annealing is based on a thermodynamic evolutionary process, whereas genetic algorithms are based on the principles of Darwin’s theory of evolution and the field […]
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A Neural Network is an Artificial Intelligence (AI) methodology that attempts to mimic the behavior of the neurons in our brains. Neural networks really shine when it comes to pattern recognition and are used in image and character recognition programs, data filtering applications, and even robotics. A neural net was even used to drive an […]
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