I will at least cover the following topics of Deep NNs: Kernels (Tangent Kernel, SVM, and machine machine representation of DNNs), Genearalization (bias variance tradeoff and double descent and complexity models and classfication trees), Generative models (GANs and half-plane cutting), AI explaination (Datamodels, Influential functions), Universal approximation theories for Shallow NNs and Deep NNs. and Un-rectifying analysis (DAG-DNN).