TensorFlow Model Optimization Toolkit-Quantization

TensorFlow Model Optimization Toolkit (TF MOT) is a set of tools designed to optimize and compress TensorFlow models. One of the most powerful features of TF MOT is quantization, which is the process of converting floating-point weights and activations in a neural network to lower-precision fixed-point numbers. This reduces the memory and computation requirements of the network, making it more efficient to run on resource-constrained devices like mobile phones and embedded systems.