The Following are the Tensorflow Tutorials:
Tutorial 1: Write a very very simple Tensorflow program code for :
- A) Add a two matrix .
- B) Inverse operation of matrix and its way of decomposition.
- C) Calculate the eigen values and eigen vectors of matrix ?
- D) Check this: GitHub Tutorial 1 .
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Tutorial 2: Write a program for basic Matrix operation ?
- A) Write a tensorflow program that pass two 1-D array of same size. The passed arrays must be have element-wise multiplication. The final result is also multiplied by constant. The program must display output?
- B) Write a tensorflow program that pass two 1-D array of same size. The passed arrays should have vector wise multiplication and provide the results. The program must display output?
- C) Write a tensorflow program that pass two 2-D array of same size. The passed arrays should have vector wise multiplication and provide the results.The program must display output?
- D) Check this: GitHub Tutorial 2
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Tutorial 3: Write a program that defines the following Activation Functions in deep learning systems?
- A) ReLU Activation Function, B) Sigmoid Activatioon Function , C) Tanh Activation Function,
D) Softsign Activation Function, E) Softplus Activation Function, F) ELU activation Fuction, G) Check this : GitHub Tutorial 3
Tutorial 4: Write a Tensor-flow code for different loss fuctions. Evaluate and display their performance results ?
- (A) Regression Loss Functions: (a) L2-norm function (Euclidean loss or mean square loss). (b) L1-norm loss function. (c) Pseudo-Hubber loss fucntion.
- (B) Classification Loss Functions: (a) Hinge Loss function, (b) Cross-entropy Loss, (c) Sigmoid Cross-entropy Loss, (d) Weighted Cross Entropy, (e) Softmax cross Entropy loss, (f) Sparse Cross-entropy Loss, (g) Check this at GitHub.
Tutorial 6: Write a Tensor-flow code for Linear Regression example. Evaluate and display their performance
- A) Matrix Inversion method. B) Back propagation optimizing way. (C) Check this: GitHub Regression Inverse Tutorial 8 , . GitHub Regression Cholesky Tutorial 8 and GitHub Regression Tensorflow way Tutoral 8 .
Tutorial 8: Write a code for Simple CNN in Tensorflow For MNIST dataset. You should have to use two hidden layers, Relu activation function and max-pooling phenomena. The Output should display the recognized dataset with resultant accuracy? Check this: GitHub CNN MNIST 1 and Github CNN MINIST 2