routine

mnist/README.md

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+# No deep learning,just function mapping
+
+$$
+X = [v_1,v_2,.....,v_{784}]\\
+X:[1,dx]
+$$
+
+$$
+H_1 = XW_{1} + b_{1} \\
+W_1:[d_1,dx] \\
+b_1:[d_1]
+$$
+
+$$
+H_2 = H_1W_2 + b_2 \\
+W_1:[d_2,d_1] \\
+b_1:[d_2]
+$$
+
+$$
+H_3=H_2W_3 + b_3 \\
+W_3:[10,d_2]\\
+b_3:[10]
+$$
+
+## Loss
+
+$$
+H_3:[1,d_3] \\
+Y:[0/1/2/.../9] \\
+eg.:1\geq[0,1,0,0,0,0,0,0,0,0,0] \\
+eg.:3\geq[0,0,0,1,0,0,0,0,0,0,0] \\
+Euclidean\ Distance:H_3\ vs\ Y
+$$
+
+
+
+## In a nutshell
+
+$$
+pred = W_3 \times \{W_2\cdot[W_1X+b_1]+b_2\}+b_3
+$$
+