MNIST-Tensorflow-Code. It contains Data Augmentaion, Strided convolution, Batch Normalization, Leaky Relu, Global Average pooling, L2 Regularization, learning rate decay, He initialization, Tensorboard, Save, Restore

Problem

The full read on this project is a sign-in away — what it solves, who it serves, and where it sits in the market.

Audience

The full read on this project is a sign-in away — what it solves, who it serves, and where it sits in the market.

Market

The full read on this project is a sign-in away — what it solves, who it serves, and where it sits in the market.

Pricing

The full read on this project is a sign-in away — what it solves, who it serves, and where it sits in the market.