gomlx

Machine learning models training and inference using GoMLX for Go. It provides an abstraction to create vectorized computation graphs, that can then be JIT-compiled (Just-In-Time) and executed very fast, with backends using XLA (for CPU/CUDA/TPU), Go and others. Includes a reach set of vector (tensors) operations on the graph, a rich ML library with various type of layers, support for training variables, optimizers, training loops, dataset iterators and more. Apply this skill when working ML projects, or needing to do very efficient vectorized (tensor) computations, like image processing, physics or chemestry simulation, etc.