deep learning with pytorch

Deep Learning without PhD, masters, graduation

Mayur Bhangale StoreKey

A Python based scientific computing package targeted at two sets of audiences:

• A replacement for numpy to use the power of GPUs • A deep learning research platform that provides maximum flexibility

and speed

Basics

Variables, Tensors, Autograd

Predictive models

Linear Regression

• Fit a line to a data set of observations • Use this line to predict unobserved values

Predictive models

Linear Regression

Input

x

Output

y

mx + c = y

Linear Function

10 20 100 200

1.3 1.2 4.5 4.8

Predictive models

Logistic Regression

• Predicts the probability of occurrence of an event by fitting data to a logit function.

• Used to predict a binary outcome (1 / 0, Yes / No, True / False) given a set of independent variables.

Predictive models

Logistic Regression

Inputx

Logits

y

mx + c = y

Linear Function

10 20

100 200

1.3 1.2 4.5 4.8

S = g(y)

SoftmaxFunction

g(y)

Softmax

0.1 0.1 0.4 0.4

D(S, L)

CrossEntropyFunction

0 0 1 1

L

True Labels

Predictive models

Input

x

Logits

y

Linear Function

SoftmaxFunction

g(y)

Softmax

D(S, L)

CrossEntropyFunction

Labels

L

True Labels

Readout LayerInput Layer Output Layer

Logistic Regression

Predictive models

Input

x

Logits

y

Linear Function

SoftmaxFunction

g(y)

Softmax

CrossEntropyFunction

Labels

L

True Labels

Readout LayerInput Layer Output Layer

ExampleSize: 784

Size: 10

Convolutional Neural Network

Thank you

Mayur Bhangale mayur@storekey.in

mayurbhangalemayurcb mayurbhangale