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• Configuring neural networks is difficult because there is no good theory on how to do it. You must be systematic and explore different configurations both from a dynamical and an objective results point of a view to try to understand what is going on for a given predictive modeling problem.
• Welcome to this neural network programming series. In this episode, we will see how we can speed up the neural network training process by utilizing the...
• Jan 03, 2020 · Machine learning is the most algorithm-intense field in computer science. Gone are those days when people had to code all algorithms for machine learning. Thanks to Python and it’s libraries, modules, and frameworks. Python machine learning libraries have grown to become the most preferred language for machine learning algorithm implementations. Let’s have a look at […]
• pytorch copy tensor, Creating tensors in PyTorch. Let's first understand what a tensor is. A scalar is a single independent value, a 1D array of values is called a vector, a 2D array of values is called a matrix, and any array of values that is more than 2D is simply called a tensor.
• One, Two and Three Dimensional Flows. Term one, two or three dimensional flow refers to the number of space coordinated required to describe a flow.
• 1.6.4.1. Brute Force¶. Fast computation of nearest neighbors is an active area of research in machine learning. The most naive neighbor search implementation involves the brute-force computation of distances between all pairs of points in the dataset: for \(N\) samples in \(D\) dimensions, this approach scales as \(O[D N^2]\).
• PyTorch is relatively new but is gaining popularity. It is also open source, primarily developed by Facebook, and is known for its simplicity, flexibility, and customizability. Recently, PyTorch has seen a high level of adoption within the deep learning framework community and is considered to be a competitor to TensorFlow (if ‘competitor ...