gorgonia.org/gorgonia (go): Package gorgonia is a library that helps facilitate machine learning in Go. Write and evaluate mathematical equations involving multidimensional arrays easily. Do differentiation with them just as easily.  Autodiff showcases automatic differentiation  Basic example of representing mathematical equations as graphs.  In this example, we want to represent the following equation  Gorgonia provides an API that is fairly idiomatic - most of the functions in in the API return (T, error). This is useful for many cases, such as an interactive shell for deep learning. However, it must also be acknowledged that this makes composing functions together a bit cumbersome.  To that end, Gorgonia provides two alternative methods. First, the `Lift` based functions; Second the `Must` function  Linear Regression Example  The formula for a straight line is  We want to find an `m` and a `c` that fits the equation well. We'll do it in both float32 and float64 to showcase the extensibility of Gorgonia   This example showcases the reasons for the more confusing functions.  This example showcases dealing with errors. This is part 2 of the raison d'être of the more complicated functions - dealing with errors  SymbolicDiff showcases symbolic differentiation
Keywords: artificial-intelligence|automatic-differentiation|computation-graph|deep-learning|deep-neural-networks|deeplearning|differentiation|go|golang|gorgonia|gradient-descent|graph-computation|hacktoberfest|machine-learning|neural-network|symbolic-differentiation