Statistical Inference Requires Sampling

Running Machine Learning Inference as Service from Scratch

Conventional Classification Loss Functions Elucidated

Model Optimization with Genetically Evolved Hyperparameters

Mathematical Foundations to Neural Network Quantization

Gated Linear Units and Gated CNN Explained

Evolution Search on Transformer Neural Network Architectures

Understand the Sparsity Introduced by Group Lasso

Fundamental Theories of Gradient Boosting Machine

Continuing to Support Frozen Graph for TensorFlow 2.x