Download presentation

Presentation is loading. Please wait.

Published byOrlando Jewitt Modified over 2 years ago

1
Theano Md. Iftekhar Tanveer Rafayet Ali Md. Iftekhar Tanveer Rafayet Ali

2
Why Theano? Machine Learning is mostly about optimization Support Vector Machine min ||Y – wX - ε|| 2 w Linear Regression

3
Why Theano? Principal Component Analysis (PCA) w min s. t. Sparse Coding / Deep Learning

4
Why Theano? A typical optimization algorithm – Gradient Descent f(x) x' f '(x') x x – γf'(x')

5
Why Theano? Typically, the user needs to hand calculate the gradient of the objective function Theano allows to calculate the gradients symbolically if you just provide the equation L (w) = #$!!@()(@($%$w Typically, the user needs to hand calculate the gradient of the objective function Theano allows to calculate the gradients symbolically if you just provide the equation L (w) = #$!!@()(@($%$w Calculate the gradient Theano!! Theano #$!!@()(@($%$

6
How It Works? Given a symbolic equation, Theano creates a graph where nodes represent variables or operator and edges represents “operated on” relationships Example: x = T.dmatrix('x') y = T.dmatrix('y') z = x + y Uses graph processing algorithms Given a symbolic equation, Theano creates a graph where nodes represent variables or operator and edges represents “operated on” relationships Example: x = T.dmatrix('x') y = T.dmatrix('y') z = x + y Uses graph processing algorithms

7
Applications/Where used? Sparse Coding Deep Learning Sparse Coding Deep Learning The optimization function becomes arbitrarily complicated based on the network and its connections. Usually solved by backpropagation Symbolic calculations make the calculation easier

8
Byproducts Computations are done in one level higher, allowing better parallelization Code is ready for GPU utilization Dynamic C code generation Speed and stability optimized Data is interpreted – so there is room for “Just in Time (JIT)” optimization Computations are done in one level higher, allowing better parallelization Code is ready for GPU utilization Dynamic C code generation Speed and stability optimized Data is interpreted – so there is room for “Just in Time (JIT)” optimization Numeric Computation Level Symbolic Computation Level Theano

9
Example Time!

Similar presentations

OK

X = 2 + t y = -3 + 2t t = x – 2 t = (y + 3)/2 x – 2 = y + 3 2 2x – 4 = y + 3 y – 2x + 7 = 0 Finding the Cartesian Equation from a vector equation x = 2.

X = 2 + t y = -3 + 2t t = x – 2 t = (y + 3)/2 x – 2 = y + 3 2 2x – 4 = y + 3 y – 2x + 7 = 0 Finding the Cartesian Equation from a vector equation x = 2.

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google

Ppt on 9-11 conspiracy theories attacks Ppt on power generation using footsteps sound Ppt on cross docking advantages Ppt on indian culture Ppt on climate change and global warming Free download ppt on training and development in hrm Ppt on creativity and innovation management Ppt on cube and cuboid volumes Ppt on limits and continuity Ppt on asian continent clip